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>> LUCAS Freitas: Hey.

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Karibu kila mtu.

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Jina langu ni Lucas Freitas.

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Mimi nina junior katika [inaudible] kusoma
sayansi ya kompyuta kwa lengo katika

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00:00:15,220 --> 00:00:16,410
computational isimu.

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00:00:16,410 --> 00:00:19,310
Hivyo sekondari wangu ni katika lugha
na nadharia ya lugha.

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00:00:19,310 --> 00:00:21,870
Mimi kwa kweli msisimko kufundisha guys
kidogo kuhusu shamba.

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Ni eneo kusisimua sana kujifunza.

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Pia pamoja na mengi ya uwezo
kwa siku zijazo.

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Kwa hiyo, mimi nina kweli msisimko kwamba guys
ni kuzingatia miradi katika

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00:00:30,160 --> 00:00:31,160
computational isimu.

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Na mimi itabidi kuwa zaidi ya furaha kwa ushauri
yoyote ya wewe kama wewe kuamua

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kujiingiza mmoja wa wale.

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>> Hivyo kwanza ya yote nini ni computational
isimu?

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Isimu hivyo computational ni
makutano kati ya lugha na

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sayansi ya kompyuta.

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Hivyo, ni nini isimu?

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Sayansi ya kompyuta ni nini?

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Vizuri kutoka lugha, nini
sisi kuchukua ni lugha.

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Hivyo isimu ni kweli utafiti
ya lugha ya asili kwa ujumla.

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Lugha hiyo asili - sisi majadiliano juu ya
lugha kwamba sisi kweli kutumia

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kuwasiliana na kila mmoja.

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Hivyo sisi ni si hasa kuzungumza
kuhusu C au Java.

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Tunazungumzia zaidi kuhusu lugha ya Kiingereza na
Lugha ya Kichina na mengine ambayo sisi

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kutumia kuwasiliana na kila mmoja.

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>> kitu changamoto juu ya ni kwamba
sasa hivi tuna karibu 7,000

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lugha katika dunia.

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Hivyo kuna aina ya juu kabisa
ya lugha ambazo tunaweza kujifunza.

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Na kisha unafikiri kwamba pengine
vigumu sana kufanya, kwa mfano,

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tafsiri kutoka lugha moja hadi
nyingine, kwa kuzingatia kwamba una

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karibu 7,000 wao.

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Hivyo, kama wewe kufikiria kufanya tafsiri ya
kutoka lugha moja hadi nyingine unaweza

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kuwa karibu zaidi ya milioni
mchanganyiko tofauti kwamba unaweza

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na kutoka lugha kwa lugha.

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Hivyo ni kweli changamoto ya kufanya baadhi ya
aina ya mfumo wa mfano tafsiri kwa

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kila lugha moja.

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>> Hivyo, lugha chipsi na syntax,
semantics, pragmatics.

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You guys si hasa haja
kujua nini ni wao.

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Lakini jambo la kuvutia sana ni kwamba
kama msemaji asili, wakati kujifunza

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lugha kama mtoto, kweli kujifunza
mambo hayo yote - semantics syntax

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na pragmatics -

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na wewe mwenyewe.

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Na hakuna mtu ana kufundisha syntax kwa
wewe kuelewa jinsi hukumu ni

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muundo.

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Hivyo, ni kweli kuvutia kwa sababu
ni kitu ambacho huja sana

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intuitively.

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>> Na nini wewe ni kuchukua kutoka
sayansi ya kompyuta?

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Naam, jambo muhimu zaidi kwamba sisi
na katika sayansi ya kompyuta ni ya kwanza ya

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wote, akili bandia
na kujifunza mashine.

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Hivyo, nini sisi ni kujaribu kufanya
computational isimu ni kufundisha

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kompyuta yako jinsi ya kufanya kitu
kwa lugha.

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>> Hivyo, kwa mfano, katika mashine
tafsiri.

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Mimi kujaribu kufundisha kompyuta yangu jinsi
kujua jinsi ya mpito kutoka moja

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lugha nyingine.

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Kwa hiyo, kimsingi kama mafundisho
kompyuta lugha mbili.

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Kama mimi kufanya usindikaji lugha ya asili,
ambayo ni kesi kwa mfano wa

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Picha ya Graph Search, kufundisha
kompyuta yako jinsi ya kuelewa

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maswali vizuri.

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>> Hivyo, kama wewe kusema "photos yangu
marafiki. "Facebook haina kutibu kwamba

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kama kamba zima ambayo ina
tu rundo la maneno.

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Ni kweli anaelewa uhusiano
kati ya "picha" na "rafiki yangu" na

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anaelewa kuwa "picha" ni
mali ya "marafiki zangu."

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>> Kwa hiyo, hiyo ni sehemu ya, kwa mfano,
usindikaji lugha ya asili.

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Ni kujaribu kuelewa nini
ni uhusiano kati ya

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00:03:04,790 --> 00:03:07,520
maneno katika sentensi.

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Na swali kubwa ni, unaweza
kufundisha kompyuta jinsi ya kuzungumza

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lugha kwa ujumla?

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Ambayo ni swali kuvutia sana
kufikiri, kama labda katika siku zijazo,

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utaenda kuwa na uwezo wa
kuzungumza na simu yako ya mkononi.

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Aina ya kama nini cha kufanya na Siri lakini
kitu zaidi kama, unaweza kweli

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kusema chochote unataka na simu
ni kwenda kuelewa kila kitu.

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Na inaweza kuwa na kufuatilia maswali
na kuendelea kuongea.

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Hiyo ni kitu kweli kusisimua,
kwa maoni yangu.

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>> Kwa hiyo, kitu kuhusu lugha ya asili.

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Kitu kweli kuvutia kuhusu
lugha ya asili ni kwamba, na hii ni

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mikopo kwa yangu Profesa wa isimu,
Maria Polinsky.

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Anatoa mfano na nadhani
ni kweli kuvutia.

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Kwa sababu sisi kujifunza lugha kutoka wakati
sisi ni kuzaliwa na kisha asili yetu

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lugha aina ya kukua kwa sisi.

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>> Na kimsingi kujifunza lugha
kutoka pembejeo ndogo, sawa?

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Wewe ni kupata tu pembejeo kutoka yako
wazazi wa lugha gani yako sauti

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kama na wewe tu kujifunza.

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Hivyo, ni ya kuvutia kwa sababu kama ukiangalia
katika hukumu hizo, kwa mfano.

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Unaweza kuangalia, "Mary unaweka juu ya kanzu kila
wakati yeye majani ya nyumba. "

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>> Katika kesi hiyo, inawezekana kuwa na
neno "yeye" rejea Mary, sawa?

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Unaweza kusema "Mary unaweka juu ya kanzu
kila wakati Mary majani

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nyumba. "ili nzuri.

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Lakini basi ukiangalia hukumu
"She unaweka juu ya koti kila wakati Mary

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majani ya nyumba. "unajua ni
haiwezekani kusema kwamba "yeye" ni

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akimaanisha Mary.

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>> Hakuna njia ya kusema kwamba "Mary unaweka
juu ya koti kila wakati Mary majani

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nyumba. "Kwa hiyo ni ya kuvutia kwa sababu
hii ni aina ya Intuition

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kwamba kila msemaji uliotokea ana.

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Na hakuna mtu alikuwa akifundisha kwamba hii ni
njia ambayo syntax kazi.

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Na kwamba unaweza tu na hii "yeye"
akimaanisha Mary katika kesi hii kwanza,

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na kwa kweli katika hii nyingine
sana, lakini si katika hili.

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Lakini kila mtu aina ya anapata
kwa jibu moja.

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Kila mmoja anakubali juu ya hilo.

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Hivyo ni kweli kuvutia jinsi ingawa
huna kujua sheria zote za

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katika lugha yako aina ya kuelewa
jinsi lugha kazi.

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>> Kwa hivyo jambo la kuvutia kuhusu asili
lugha ni kwamba huna kwa

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kujua syntax yoyote kujua kama hukumu
ni sarufi au ungrammatical kwa

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kesi nyingi.

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00:05:08,810 --> 00:05:13,220
Ambayo inafanya unafikiri kwamba labda nini
kinatokea ni kwamba kwa njia ya maisha yako,

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tu kuweka kupata zaidi na zaidi
hukumu aliiambia na wewe.

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Na kisha kuweka kukariri
yote ya hukumu.

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Na wakati mtu anakwambia
kitu, kusikia kwamba hukumu na

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ukiangalia msamiati wako
ya hukumu na kuona kama

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hukumu hiyo ni huko.

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Na kama ni huko
kusema ni sarufi.

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Kama siyo, unaweza kusema ni
ungrammatical.

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>> Hivyo, katika kesi hiyo, kusema, oh,
hivyo una orodha kubwa ya yote

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iwezekanavyo hukumu.

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Na kisha wakati wewe kusikia hukumu,
unajua kama ni sarufi au

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si kwa kuzingatia kwamba.

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jambo ni kwamba kama ukiangalia
hukumu, kwa mfano, "

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tano inaongozwa CS50 TFS kupikwa kipofu
octopus kutumia DAPA mug. "Ni

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dhahiri si hukumu ya
kwamba kusikia kabla.

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Lakini wakati huo huo unajua ni
pretty much sarufi, sawa?

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Hakuna makosa ya kisarufi
na unaweza kusema kwamba

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ni hukumu iwezekanavyo.

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>> Hivyo inafanya sisi kufikiri kwamba kweli
njia ambayo sisi kujifunza lugha ni si tu

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kwa kuwa database kubwa ya uwezekano wa
maneno au sentensi, lakini zaidi ya

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kuelewa uhusiano kati ya
maneno katika hukumu hizo.

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Je, hiyo mantiki?

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Kwa hiyo, basi swali ni, unaweza
kompyuta kujifunza lugha?

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Je, sisi kufundisha lugha ya kompyuta?

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>> Kwa hiyo, hebu fikiria ya tofauti
kati ya msemaji asili ya lugha

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na kompyuta.

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Hivyo, nini kinatokea kwa msemaji?

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Naam, msemaji uliotokea kujifunza
lugha kutoka yatokanayo na yake.

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00:06:30,430 --> 00:06:34,200
Kawaida utoto wake mapema miaka.

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Kwa hiyo, kimsingi, wewe tu kuwa na mtoto,
na kuweka kuzungumza na hayo, na

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tu kujifunza jinsi ya kuzungumza
lugha, haki?

137
00:06:40,540 --> 00:06:42,660
Hivyo, wewe ni kimsingi kutoa
pembejeo kwa mtoto.

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00:06:42,660 --> 00:06:45,200
Kwa hiyo, basi unaweza kusema kwamba kompyuta
unaweza kufanya kitu kimoja, sawa?

139
00:06:45,200 --> 00:06:49,510
Unaweza tu kutoa lugha
kama pembejeo kwa kompyuta.

140
00:06:49,510 --> 00:06:53,410
>> Kama kwa mfano kundi la files
kuwa na vitabu katika lugha ya Kiingereza.

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Labda hiyo ndiyo njia moja kwamba
inaweza uwezekano wa kufundisha

142
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kompyuta Kiingereza, right?

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Na kwa kweli, kama wewe kufikiri juu yake,
inachukua wewe labda michache

144
00:07:01,000 --> 00:07:02,680
siku ya kusoma kitabu.

145
00:07:02,680 --> 00:07:05,760
Kwa ajili ya kompyuta inachukua pili kwa
kuangalia maneno yote katika kitabu.

146
00:07:05,760 --> 00:07:10,810
Hivyo unaweza kufikiri kwamba inaweza kuwa tu hii
Hoja ya pembejeo kutoka kwa karibu na wewe,

147
00:07:10,810 --> 00:07:15,440
hiyo haitoshi kusema kwamba hiyo ni
kitu ambacho binadamu tu anaweza kufanya.

148
00:07:15,440 --> 00:07:17,680
Unaweza kufikiria kompyuta
pia wanaweza kupata pembejeo.

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00:07:17,680 --> 00:07:21,170
>> Jambo la pili ni kwamba wasemaji
pia na ubongo ambayo ina

150
00:07:21,170 --> 00:07:23,870
kujifunza lugha uwezo.

151
00:07:23,870 --> 00:07:27,020
Lakini kama wewe kufikiri juu yake,
ubongo ni jambo imara.

152
00:07:27,020 --> 00:07:30,450
Wakati wewe ni kuzaliwa, ni tayari kuweka -

153
00:07:30,450 --> 00:07:31,320
hii ni ubongo wako.

154
00:07:31,320 --> 00:07:34,660
Na kama wewe kukua, wewe tu kupata zaidi
mchango wa lugha na labda virutubisho

155
00:07:34,660 --> 00:07:35,960
na mambo mengine.

156
00:07:35,960 --> 00:07:38,170
Lakini pretty much ubongo wako
ni kitu kigumu.

157
00:07:38,170 --> 00:07:41,290
>> Hivyo unaweza kusema, vizuri, labda unaweza
kujenga kompyuta ambayo ina rundo la

158
00:07:41,290 --> 00:07:45,890
kazi na mbinu tu ya kuiga
kujifunza lugha uwezo.

159
00:07:45,890 --> 00:07:49,630
Hivyo kwa mantiki hiyo, unaweza kusema, vizuri, mimi
unaweza kuwa na kompyuta ambayo ina wote

160
00:07:49,630 --> 00:07:52,270
mambo mimi haja ya kujifunza lugha.

161
00:07:52,270 --> 00:07:56,200
Na jambo la mwisho ni kwamba asili
msemaji kujifunza kutoka kwa majaribio na makosa.

162
00:07:56,200 --> 00:08:01,090
Hivyo kimsingi jambo lingine muhimu katika
kujifunza lugha ni kwamba aina

163
00:08:01,090 --> 00:08:05,340
ya kujifunza mambo kwa kufanya
generalizations ya nini kusikia.

164
00:08:05,340 --> 00:08:10,280
>> Hivyo kama wewe ni kupanda juu kujifunza kwamba
baadhi ya maneno ni zaidi kama majina,

165
00:08:10,280 --> 00:08:11,820
baadhi wale wengine ni sifa.

166
00:08:11,820 --> 00:08:14,250
Na huna kuwa na yoyote
maarifa ya isimu

167
00:08:14,250 --> 00:08:15,040
kuelewa kwamba.

168
00:08:15,040 --> 00:08:18,560
Lakini wewe tu kujua kuna baadhi ya maneno
ni nafasi nzuri katika baadhi ya sehemu ya

169
00:08:18,560 --> 00:08:22,570
hukumu na baadhi ya watu wengine katika nchi nyingine
sehemu ya hukumu.

170
00:08:22,570 --> 00:08:26,110
>> Na kwamba wakati wa kufanya kitu ambacho ni
kama hukumu hiyo ni si sahihi -

171
00:08:26,110 --> 00:08:28,770
labda kwa sababu ya zaidi ya generalization
kwa mfano.

172
00:08:28,770 --> 00:08:32,210
Labda wakati wewe ni kupanda juu, taarifa
kwamba wingi ni kawaida

173
00:08:32,210 --> 00:08:35,809
sumu kwa kuweka S katika
mwisho wa neno.

174
00:08:35,809 --> 00:08:40,042
Na kisha kujaribu kufanya wingi wa
"Deer" kama "deers" au "jino" kama

175
00:08:40,042 --> 00:08:44,780
"Tooths." Hivyo basi wazazi wako au
mtu husahihisha wewe na anasema, hapana,

176
00:08:44,780 --> 00:08:49,020
wingi wa "deer" ni "kulungu," na
wingi wa "jino" ni "meno." Na kisha

177
00:08:49,020 --> 00:08:50,060
kujifunza mambo hayo.

178
00:08:50,060 --> 00:08:51,520
Hivyo kujifunza kutoka kwa majaribio na makosa.

179
00:08:51,520 --> 00:08:53,100
>> Lakini pia unaweza kufanya hivyo
na kompyuta.

180
00:08:53,100 --> 00:08:55,310
Unaweza kuwa na kitu kinachoitwa
kuimarisha kujifunza.

181
00:08:55,310 --> 00:08:58,560
Ambayo kimsingi ni kama kutoa
kompyuta malipo wakati wowote haina

182
00:08:58,560 --> 00:08:59,410
kitu kwa usahihi.

183
00:08:59,410 --> 00:09:04,710
Na kutoa kinyume cha malipo
na wakati gani kitu kibaya.

184
00:09:04,710 --> 00:09:07,410
Unaweza kweli kuona kwamba kama wewe kwenda
kwa Google Tafsiri na wewe kujaribu

185
00:09:07,410 --> 00:09:10,220
kutafsiri hukumu, ni
anauliza kwa maoni.

186
00:09:10,220 --> 00:09:13,240
Hivyo kama wewe kusema, oh, kuna bora
tafsiri kwa adhabu hii.

187
00:09:13,240 --> 00:09:18,140
Unaweza aina it up na kisha kama mengi ya
watu kuendelea kusema kwamba ni bora

188
00:09:18,140 --> 00:09:21,560
tafsiri, ni tu kujifunza kwamba ni
lazima kutumia tafsiri badala ya

189
00:09:21,560 --> 00:09:22,960
moja ilikuwa kutoa.

190
00:09:22,960 --> 00:09:28,830
>> Hivyo, ni suala falsafa sana
kuona kama kompyuta ni kwenda kuwa

191
00:09:28,830 --> 00:09:30,340
uwezo wa kuzungumza au si katika siku zijazo.

192
00:09:30,340 --> 00:09:34,440
Lakini Nina matumaini makubwa kwamba wanaweza
tu kwa kuzingatia hoja hizo.

193
00:09:34,440 --> 00:09:38,570
Lakini ni tu zaidi ya falsafa
swali.

194
00:09:38,570 --> 00:09:43,460
>> Hivyo wakati kompyuta bado hawezi kuzungumza,
nini ni mambo ambayo tunaweza kufanya?

195
00:09:43,460 --> 00:09:47,070
Baadhi ya mambo ya kweli ya baridi ni
data uainishaji.

196
00:09:47,070 --> 00:09:53,210
Hivyo, kwa mfano, you guys kujua
kwamba huduma ya barua pepe kufanya, kwa

197
00:09:53,210 --> 00:09:55,580
mfano, spam filtering.

198
00:09:55,580 --> 00:09:59,070
Hivyo wakati wowote kupokea spam, ni
anajaribu kuchuja kwa sanduku mwingine.

199
00:09:59,070 --> 00:10:00,270
Hivyo ni jinsi gani kufanya hivyo?

200
00:10:00,270 --> 00:10:06,080
Siyo kama kompyuta tu anajua
anwani nini email ni kutuma spam.

201
00:10:06,080 --> 00:10:09,130
Hivyo ni zaidi ya msingi juu ya maudhui ya
ujumbe, au labda cheo, au

202
00:10:09,130 --> 00:10:11,310
labda baadhi mfano kwamba wewe.

203
00:10:11,310 --> 00:10:15,690
>> Kwa hiyo, kimsingi, nini unaweza kufanya kupata ni
mengi ya data ya barua pepe kwamba ni spam,

204
00:10:15,690 --> 00:10:19,980
barua pepe ambayo ni si spam, na kujifunza nini
aina ya mifumo una katika

205
00:10:19,980 --> 00:10:21,000
wale ambao ni spam.

206
00:10:21,000 --> 00:10:23,260
Na hii ni sehemu ya computational
isimu.

207
00:10:23,260 --> 00:10:24,720
Ni wito data uainishaji.

208
00:10:24,720 --> 00:10:28,100
Na sisi ni kweli kwenda kuona
mfano wa kwamba katika slides ijayo.

209
00:10:28,100 --> 00:10:32,910
>> Jambo la pili ni lugha ya asili
usindikaji ambayo ni kitu

210
00:10:32,910 --> 00:10:36,580
Graph Tafuta ni kufanya ya kuruhusu
kuandika hukumu.

211
00:10:36,580 --> 00:10:38,690
Na amana wewe kuelewa nini
ni maana na inatoa

212
00:10:38,690 --> 00:10:39,940
wewe matokeo bora.

213
00:10:39,940 --> 00:10:43,880
Kwa kweli, kama wewe kwenda Google au Bing
na wewe kutafuta kitu kama Lady

214
00:10:43,880 --> 00:10:47,060
Urefu Gaga, wewe ni kweli kwenda
kupata 5 '1 "badala ya habari

215
00:10:47,060 --> 00:10:50,170
kutoka kwake kwa sababu ni kweli anaelewa
nini wewe kuzungumza juu.

216
00:10:50,170 --> 00:10:52,140
Hivyo kwamba ni sehemu ya asili
usindikaji lugha.

217
00:10:52,140 --> 00:10:57,000
>> Au pia wakati unatumia Siri, kwanza
una algorithm ambayo inajaribu

218
00:10:57,000 --> 00:11:01,130
kutafsiri unachosema
katika maneno, katika maandishi.

219
00:11:01,130 --> 00:11:03,690
Na kisha anajaribu kutafsiri
kwamba katika maana.

220
00:11:03,690 --> 00:11:06,570
Ili wote sehemu ya asili
usindikaji lugha.

221
00:11:06,570 --> 00:11:08,320
>> Kisha una mashine tafsiri -

222
00:11:08,320 --> 00:11:10,300
ambayo ni kweli moja
ya favorites yangu -

223
00:11:10,300 --> 00:11:14,060
ambayo ni kutafsiri tu kutoka
lugha na mwingine.

224
00:11:14,060 --> 00:11:17,950
Hivyo unaweza kufikiri kwamba wakati unafanya
tafsiri mashine, una

225
00:11:17,950 --> 00:11:19,750
uwezekano usio wa hukumu.

226
00:11:19,750 --> 00:11:22,960
Hivyo hakuna njia ya kuhifadhi tu
kila tafsiri moja.

227
00:11:22,960 --> 00:11:27,440
Hivyo kuwa na kuja na kuvutia
algorithms kuwa na uwezo wa

228
00:11:27,440 --> 00:11:30,110
kutafsiri kila moja
hukumu kwa namna fulani.

229
00:11:30,110 --> 00:11:32,483
>> You guys una maswali yoyote hadi sasa?

230
00:11:32,483 --> 00:11:34,450
No?

231
00:11:34,450 --> 00:11:34,830
OK.

232
00:11:34,830 --> 00:11:36,900
>> Basi ni nini sisi kwenda kuona leo?

233
00:11:36,900 --> 00:11:39,300
Awali ya yote, mimi nina kwenda kuzungumza kuhusu
Uainishaji tatizo.

234
00:11:39,300 --> 00:11:41,440
Hivyo moja kwamba nilikuwa
kusema kuhusu spam.

235
00:11:41,440 --> 00:11:46,820
Nini mimi kwenda kufanya ni, kutokana na lyrics
wimbo, unaweza kujaribu kufikiri

236
00:11:46,820 --> 00:11:49,810
na uwezekano mkubwa
ambao ni muimbaji?

237
00:11:49,810 --> 00:11:53,590
Hebu kusema kwamba nina nyimbo kutoka Lady
Gaga na Katy Perry, kama mimi kukupa

238
00:11:53,590 --> 00:11:58,130
wimbo mpya, unaweza kufikiri kama
ni Katy Perry au Lady Gaga?

239
00:11:58,130 --> 00:12:01,490
>> moja ya pili, Mimi tu kwenda kuzungumza
kuhusu tatizo segmentation.

240
00:12:01,490 --> 00:12:05,780
Basi, mimi sijui kama nyie kujua, lakini
China, Japan, wengine Asia ya Mashariki

241
00:12:05,780 --> 00:12:08,090
lugha, na lugha nyingine
kwa ujumla, hawana

242
00:12:08,090 --> 00:12:09,830
nafasi kati ya maneno.

243
00:12:09,830 --> 00:12:13,540
Na kisha kama unadhani kuhusu njia ambayo
kompyuta ya aina yako ya inajaribu kwa

244
00:12:13,540 --> 00:12:18,600
kuelewa usindikaji lugha ya asili,
inaonekana katika maneno na

245
00:12:18,600 --> 00:12:21,500
anajaribu kuelewa uhusiano
kati yao, sawa?

246
00:12:21,500 --> 00:12:25,440
Lakini basi kama una Kichina, na
kuwa na nafasi zero, ni ngumu kweli kweli

247
00:12:25,440 --> 00:12:28,360
kujua nini ni uhusiano kati ya
maneno, kwa sababu wao hawana

248
00:12:28,360 --> 00:12:29,530
maneno ya kwanza.

249
00:12:29,530 --> 00:12:32,600
Hivyo kufanya kitu kinachoitwa
segmentation ambayo ina maana ya kuweka

250
00:12:32,600 --> 00:12:36,490
nafasi kati ya kile tunatarajia kuwaita
maneno katika lugha hizo.

251
00:12:36,490 --> 00:12:37,740
Mantiki?

252
00:12:37,740 --> 00:12:39,680

253
00:12:39,680 --> 00:12:41,540
>> Na kisha tunakwenda
majadiliano juu ya syntax.

254
00:12:41,540 --> 00:12:44,050
Hivyo tu kidogo kuhusu asili
usindikaji lugha.

255
00:12:44,050 --> 00:12:45,420
Ni kwenda kuwa tu maelezo ya jumla.

256
00:12:45,420 --> 00:12:50,700
Kwa hiyo leo, kimsingi nini nataka kufanya
ni kukupa guys kidogo ya

257
00:12:50,700 --> 00:12:53,930
ndani ya nini ni uwezekano
kwamba unaweza kufanya na computational

258
00:12:53,930 --> 00:12:54,960
isimu.

259
00:12:54,960 --> 00:13:00,410
Na kisha unaweza kuona nini unafikiri
ni baridi kati ya mambo hayo.

260
00:13:00,410 --> 00:13:02,270
Na labda unaweza kufikiria mradi
na kuja kuzungumza na mimi.

261
00:13:02,270 --> 00:13:05,260
Na mimi siwezi kutoa ushauri
juu ya jinsi ya kutekeleza.

262
00:13:05,260 --> 00:13:09,060
>> Hivyo syntax ni kwenda kuwa kidogo
kuhusu Graph Search na mashine

263
00:13:09,060 --> 00:13:09,670
tafsiri.

264
00:13:09,670 --> 00:13:13,650
Mimi tu kwenda kutoa mfano wa jinsi
unaweza, kwa mfano, kutafsiri

265
00:13:13,650 --> 00:13:16,020
kitu kutoka Ureno kwa lugha ya Kiingereza.

266
00:13:16,020 --> 00:13:17,830
Sauti nzuri?

267
00:13:17,830 --> 00:13:19,293
>> Hivyo kwanza, tatizo uainishaji.

268
00:13:19,293 --> 00:13:23,590
Mimi itabidi kusema kwamba sehemu hii ya semina
ni kwenda kuwa magumu sana

269
00:13:23,590 --> 00:13:27,560
moja kwa sababu tu kuna kwenda
kuwa baadhi ya coding.

270
00:13:27,560 --> 00:13:29,470
Lakini ni kwenda kuwa Python.

271
00:13:29,470 --> 00:13:34,380
Mimi najua wewe guys sijui Python, hivyo
Mimi tu kwenda kueleza juu

272
00:13:34,380 --> 00:13:35,750
ngazi ya nini mimi kufanya.

273
00:13:35,750 --> 00:13:40,900
Na huna kwa kweli huduma pia
mengi kuhusu syntax kwa sababu hiyo ni

274
00:13:40,900 --> 00:13:42,140
kitu guys wanaweza kujifunza.

275
00:13:42,140 --> 00:13:42,540
OK?

276
00:13:42,540 --> 00:13:43,580
Sauti nzuri.

277
00:13:43,580 --> 00:13:46,020
>> Kwa hiyo kile ni tatizo uainishaji?

278
00:13:46,020 --> 00:13:49,140
Hivyo wewe ni kutokana na baadhi ya lyrics kwa
song na unataka nadhani

279
00:13:49,140 --> 00:13:50,620
ambaye ni kuimba.

280
00:13:50,620 --> 00:13:54,045
Na hii inaweza kuwa kwa aina yoyote
ya matatizo mengine.

281
00:13:54,045 --> 00:13:59,980
Hivyo inaweza kuwa, kwa mfano, una
kampeni ya urais na una

282
00:13:59,980 --> 00:14:02,610
hotuba, na unataka kupata
nje kama ilikuwa, kwa mfano,

283
00:14:02,610 --> 00:14:04,470
Obama au Mitt Romney.

284
00:14:04,470 --> 00:14:07,700
Au unaweza kuwa na rundo la barua pepe na
unataka kufikiri kama wao ni

285
00:14:07,700 --> 00:14:08,890
spam au la.

286
00:14:08,890 --> 00:14:11,440
Hivyo ni kuainisha baadhi tu
data ya msingi juu ya maneno

287
00:14:11,440 --> 00:14:13,790
kwamba una huko.

288
00:14:13,790 --> 00:14:16,295
>> Kufanya hivyo kwamba, una
kufanya baadhi ya mawazo.

289
00:14:16,295 --> 00:14:20,570
Hivyo mengi kuhusu computational isimu
ni kufanya mawazo,

290
00:14:20,570 --> 00:14:24,100
mawazo kawaida smart, ili
unaweza kupata matokeo mazuri.

291
00:14:24,100 --> 00:14:26,670
Kujaribu kujenga mfano wa kuigwa kwa ajili yake.

292
00:14:26,670 --> 00:14:31,290
Na kisha kujaribu nje na kuona kama ni kazi,
kama anatoa usahihi nzuri.

293
00:14:31,290 --> 00:14:33,940
Na kama itakuwa hivyo, basi
kujaribu kuboresha yake.

294
00:14:33,940 --> 00:14:37,640
Kama hana, wewe ni kama, OK, labda mimi
wanapaswa kufanya dhana tofauti.

295
00:14:37,640 --> 00:14:44,030
>> Hivyo dhana kwamba tunakwenda
kufanya ni kwamba msanii kawaida kuimba

296
00:14:44,030 --> 00:14:49,220
kuhusu mada mara nyingi, na labda
anatumia maneno mara nyingi tu

297
00:14:49,220 --> 00:14:50,270
kwa sababu wao ni kutumika yake.

298
00:14:50,270 --> 00:14:51,890
Unaweza kufikiri tu ya rafiki yako.

299
00:14:51,890 --> 00:14:57,350
Mimi nina uhakika guys wote kuwa na marafiki
kwamba kusema saini zao maneno,

300
00:14:57,350 --> 00:14:59,260
literally kwa kila sentensi moja -

301
00:14:59,260 --> 00:15:02,660
kama baadhi neno maalum au baadhi maalum
maneno ya kwamba wanasema kwa

302
00:15:02,660 --> 00:15:04,020
kila sentensi moja.

303
00:15:04,020 --> 00:15:07,920
>> Na nini unaweza kusema ni kwamba kama unaweza kuona
hukumu ambayo ina sahihi

304
00:15:07,920 --> 00:15:11,450
maneno, unaweza nadhani kwamba pengine
rafiki yako ni

305
00:15:11,450 --> 00:15:13,310
moja kusema kuwa, right?

306
00:15:13,310 --> 00:15:18,410
Hivyo kudhani kuwa na kisha
kwamba ni jinsi gani kujenga mfano wa kuigwa.

307
00:15:18,410 --> 00:15:24,440
>> mfano kwamba mimi nina kwenda kutoa ni juu ya
jinsi Lady Gaga, kwa mfano, watu

308
00:15:24,440 --> 00:15:27,430
kusema kwamba anatumia "mtoto" kwa
yake yote namba moja nyimbo.

309
00:15:27,430 --> 00:15:32,270
Na kwa kweli hii ni video ambayo inaonyesha
yake akisema neno "mtoto" kwa

310
00:15:32,270 --> 00:15:33,410
nyimbo mbalimbali.

311
00:15:33,410 --> 00:15:33,860
>> [Video avspelning]

312
00:15:33,860 --> 00:15:34,310
>> - (KUIMBA) Baby.

313
00:15:34,310 --> 00:15:36,220
Baby.

314
00:15:36,220 --> 00:15:37,086
Baby.

315
00:15:37,086 --> 00:15:37,520
Baby.

316
00:15:37,520 --> 00:15:37,770
Baby.

317
00:15:37,770 --> 00:15:38,822
Babe.

318
00:15:38,822 --> 00:15:39,243
Baby.

319
00:15:39,243 --> 00:15:40,085
Baby.

320
00:15:40,085 --> 00:15:40,510
Baby.

321
00:15:40,510 --> 00:15:40,850
Baby.

322
00:15:40,850 --> 00:15:41,090
>> [Mwisho video avspelning-

323
00:15:41,090 --> 00:15:44,020
>> LUCAS Freitas: Hivyo kuna, nadhani,
40 nyimbo hapa katika ambayo anasema

324
00:15:44,020 --> 00:15:48,690
neno "mtoto." Hivyo unaweza kimsingi nadhani
kwamba kama unaweza kuona wimbo ambayo ina

325
00:15:48,690 --> 00:15:52,180
neno "mtoto," kuna baadhi ya high
uwezekano kwamba ni Lady Gaga.

326
00:15:52,180 --> 00:15:56,450
Lakini hebu jaribu kuendeleza hii
zaidi zaidi rasmi.

327
00:15:56,450 --> 00:16:00,470
>> Basi hizi ni lyrics kwa nyimbo na
Lady Gaga na Katy Perry.

328
00:16:00,470 --> 00:16:04,120
Hivyo ukiangalia Lady Gaga, unaweza kuona wao
kuwa na mengi ya matukio ya "mtoto," a

329
00:16:04,120 --> 00:16:07,710
mengi ya matukio ya "njia." Na kisha
Katy Perry ina mengi ya matukio ya

330
00:16:07,710 --> 00:16:10,360
"," Mengi ya matukio ya "moto."

331
00:16:10,360 --> 00:16:14,560
>> Hivyo kimsingi ni nini tunataka
kufanya ni, unaweza kupata lyric.

332
00:16:14,560 --> 00:16:20,480
Hebu kusema kwamba, kupata lyric kwa
wimbo kuwa ni "mtoto," tu "mtoto." Kama

333
00:16:20,480 --> 00:16:24,750
wewe tu kupata neno "mtoto," na hii
ni data yote una kutoka

334
00:16:24,750 --> 00:16:27,880
Lady Gaga na Katy Perry, ambao
wewe nadhani ni mtu

335
00:16:27,880 --> 00:16:29,370
ambao kuimba wimbo?

336
00:16:29,370 --> 00:16:32,360
Lady Gaga au Katy Perry?

337
00:16:32,360 --> 00:16:33,150
Lady Gaga, sawa?

338
00:16:33,150 --> 00:16:37,400
Kwa sababu yeye ni mmoja tu ambaye anasema
"Mtoto." Hii inaonekana kijinga, sawa?

339
00:16:37,400 --> 00:16:38,760
OK, hii ni kweli ni rahisi.

340
00:16:38,760 --> 00:16:41,860
Mimi tu kuangalia nyimbo mbili na
Bila shaka, yeye ni mmoja tu ambaye ana

341
00:16:41,860 --> 00:16:42,660
"Mtoto."

342
00:16:42,660 --> 00:16:44,740
>> Lakini nini kama wewe kuwa na rundo la maneno?

343
00:16:44,740 --> 00:16:50,900
Kama una halisi lyric, kitu
kama, "mtoto, I just

344
00:16:50,900 --> 00:16:51,610
akaenda kuona [? CFT?]

345
00:16:51,610 --> 00:16:54,020
hotuba, "au kitu kama hicho, na
basi kweli kuwa na takwimu nje -

346
00:16:54,020 --> 00:16:55,780
msingi maneno hayo yote -

347
00:16:55,780 --> 00:16:58,350
ambao ni msanii ambaye pengine
kuimba wimbo huu?

348
00:16:58,350 --> 00:17:01,860
Basi hebu kujaribu kuendeleza
hii kidogo zaidi.

349
00:17:01,860 --> 00:17:05,630
>> OK, hivyo msingi tu juu ya data kwamba sisi
got, inaonekana kwamba Gaga pengine ni

350
00:17:05,630 --> 00:17:06,260
mwimbaji.

351
00:17:06,260 --> 00:17:07,904
Lakini jinsi gani tunaweza kuandika
hii rasmi zaidi?

352
00:17:07,904 --> 00:17:10,579

353
00:17:10,579 --> 00:17:13,140
Na kuna kwenda kuwa ni kidogo
kidogo ya takwimu.

354
00:17:13,140 --> 00:17:15,880
Hivyo kama wewe kupotea, kujaribu tu
kuelewa dhana.

355
00:17:15,880 --> 00:17:18,700
Haijalishi kama wewe kuelewa
equations kikamilifu vizuri.

356
00:17:18,700 --> 00:17:22,150
Hii yote ni kwenda kuwa online.

357
00:17:22,150 --> 00:17:25,490
>> Hivyo kimsingi nini mimi kuhesabu ni
uwezekano kwamba wimbo huu ni kwa

358
00:17:25,490 --> 00:17:28,040
Lady Gaga kutokana na kwamba -

359
00:17:28,040 --> 00:17:30,660
hivyo bar hii ina maana kutokana na kwamba -

360
00:17:30,660 --> 00:17:33,680
Niliona neno "mtoto."
Je, hiyo mantiki?

361
00:17:33,680 --> 00:17:35,540
Basi, mimi nina kujaribu mahesabu ya
kwamba uwezekano.

362
00:17:35,540 --> 00:17:38,540
>> Kwa hiyo, kuna theorem hii inayoitwa
Bayes theorem kwamba anasema kwamba

363
00:17:38,540 --> 00:17:43,330
uwezekano wa B aliyopewa, ni
uwezekano wa B kutolewa, mara

364
00:17:43,330 --> 00:17:47,660
uwezekano wa A, juu ya uwezekano
ya B. Hii ni equation kwa muda mrefu.

365
00:17:47,660 --> 00:17:51,970
Lakini nini una kuelewa kutoka
ni kwamba hii ni nini nataka

366
00:17:51,970 --> 00:17:52,830
mahesabu, right?

367
00:17:52,830 --> 00:17:56,570
Hivyo uwezekano kwamba wimbo ni kwa
Lady Gaga kutokana na kwamba Niliona neno

368
00:17:56,570 --> 00:17:58,230
"Mtoto."

369
00:17:58,230 --> 00:18:02,960
>> Na sasa nini mimi kupata ni
uwezekano wa neno "mtoto" kutokana na

370
00:18:02,960 --> 00:18:04,390
kwamba mimi na Lady Gaga.

371
00:18:04,390 --> 00:18:07,220
Na kile ambacho ni kwamba kimsingi?

372
00:18:07,220 --> 00:18:10,500
Nini maana ya ni, ni nini
uwezekano wa kuona neno "mtoto"

373
00:18:10,500 --> 00:18:12,130
katika Gaga lyrics?

374
00:18:12,130 --> 00:18:16,240
Kama nataka kufanya mahesabu kwamba katika sana
njia rahisi, ni tu ya idadi ya

375
00:18:16,240 --> 00:18:23,640
mara Mimi naona "mtoto" juu ya idadi ya jumla
ya maneno katika Gaga lyrics, sawa?

376
00:18:23,640 --> 00:18:27,600
Ni frequency kwamba mimi kuona nini
kwamba neno katika kazi Gaga ya?

377
00:18:27,600 --> 00:18:30,530
Mantiki?

378
00:18:30,530 --> 00:18:33,420
>> awamu ya pili ni
uwezekano wa Gaga.

379
00:18:33,420 --> 00:18:34,360
Hiyo ina maana gani?

380
00:18:34,360 --> 00:18:38,550
Kwamba kimsingi ina maana, ni nini
uwezekano wa kuainisha

381
00:18:38,550 --> 00:18:40,690
baadhi lyrics kama Gaga?

382
00:18:40,690 --> 00:18:45,320
Na kwamba ni aina ya weird, lakini
hebu fikiria ya mfano.

383
00:18:45,320 --> 00:18:49,230
Basi hebu kusema kwamba uwezekano wa
kuwa "mtoto" katika wimbo ni sawa

384
00:18:49,230 --> 00:18:51,760
kwa Gaga na Britney Spears.

385
00:18:51,760 --> 00:18:54,950
Lakini Britney Spears ina mara mbili
zaidi ya nyimbo Lady Gaga.

386
00:18:54,950 --> 00:19:00,570
Hivyo kama mtu nasibu tu inakupa
lyrics ya "mtoto," Jambo la kwanza

387
00:19:00,570 --> 00:19:04,710
kuangalia ni, ni nini uwezekano wa
kuwa "mtoto" katika Gaga wimbo, "mtoto"

388
00:19:04,710 --> 00:19:05,410
katika Britney wimbo?

389
00:19:05,410 --> 00:19:06,460
Na kitu kimoja.

390
00:19:06,460 --> 00:19:10,040
>> Kwa hivyo jambo la pili kwamba utaona ni,
vizuri, ni nini uwezekano wa

391
00:19:10,040 --> 00:19:13,770
lyric hii na yenyewe kuwa Gaga lyric,
na ni nini uwezekano wa

392
00:19:13,770 --> 00:19:15,380
kuwa Britney lyric?

393
00:19:15,380 --> 00:19:18,950
Hivyo tangu Britney ina watu wengi zaidi lyrics
kuliko Gaga, ungekuwa pengine

394
00:19:18,950 --> 00:19:21,470
kusema, vizuri, hii pengine ni
Britney lyric.

395
00:19:21,470 --> 00:19:23,340
Hivyo ndiyo sababu tuna hii
Muda hapa.

396
00:19:23,340 --> 00:19:24,670
Uwezekano wa Gaga.

397
00:19:24,670 --> 00:19:26,950
Hufanya akili?

398
00:19:26,950 --> 00:19:28,660
Gani?

399
00:19:28,660 --> 00:19:29,370
OK.

400
00:19:29,370 --> 00:19:33,500
>> Na ile ya mwisho ni uwezekano
ya "mtoto" ambayo haina

401
00:19:33,500 --> 00:19:34,810
kweli jambo hilo sana.

402
00:19:34,810 --> 00:19:39,940
Lakini ni uwezekano wa
kuona "mtoto" katika lugha ya Kiingereza.

403
00:19:39,940 --> 00:19:42,725
Sisi kwa kawaida hawajali kwamba
mengi kuhusu muda huo.

404
00:19:42,725 --> 00:19:44,490
Je, hiyo mantiki?

405
00:19:44,490 --> 00:19:48,110
Hivyo uwezekano wa Gaga ni
aitwaye uwezekano kabla ya

406
00:19:48,110 --> 00:19:49,530
ya Gaga darasa.

407
00:19:49,530 --> 00:19:53,840
Kwa sababu maana yake ni kwamba tu, ni nini
uwezekano wa kuwa na darasa kwamba -

408
00:19:53,840 --> 00:19:55,520
ambayo ni Gaga -

409
00:19:55,520 --> 00:19:59,350
tu kwa ujumla, tu
bila masharti.

410
00:19:59,350 --> 00:20:02,560
>> Na kisha wakati mimi na uwezekano wa
Gaga kupewa "mtoto," tunasema pamoja na

411
00:20:02,560 --> 00:20:06,160
teary uwezekano kwa sababu ni
uwezekano wa kuwa na

412
00:20:06,160 --> 00:20:08,300
Gaga kutokana na baadhi ya ushahidi.

413
00:20:08,300 --> 00:20:11,050
Hivyo mimi nina kutoa ushahidi
kwamba Niliona neno mtoto na

414
00:20:11,050 --> 00:20:12,690
wimbo mantiki?

415
00:20:12,690 --> 00:20:15,960

416
00:20:15,960 --> 00:20:16,410
OK.

417
00:20:16,410 --> 00:20:22,400
>> Hivyo Kama mimi mahesabu kwamba kwa kila
ya nyimbo kwa ajili ya Lady Gaga,

418
00:20:22,400 --> 00:20:25,916
yale ambayo itakuwa -

419
00:20:25,916 --> 00:20:27,730
inaonekana, siwezi hoja hii.

420
00:20:27,730 --> 00:20:31,850

421
00:20:31,850 --> 00:20:36,920
uwezekano wa Gaga itakuwa
kitu kama, 2 zaidi ya 24, mara 1/2,

422
00:20:36,920 --> 00:20:38,260
zaidi ya 2 juu ya 53.

423
00:20:38,260 --> 00:20:40,640
Haijalishi kama unajua nini
namba hizi ni kuja kutoka.

424
00:20:40,640 --> 00:20:44,750
Lakini ni idadi tu kwamba ni kwenda
kuwa zaidi ya 0, sawa?

425
00:20:44,750 --> 00:20:48,610
>> Na kisha wakati mimi kufanya Katy Perry,
uwezekano wa "mtoto" kutokana na Katy ni

426
00:20:48,610 --> 00:20:49,830
tayari 0, sawa?

427
00:20:49,830 --> 00:20:52,820
Kwa sababu hakuna "mtoto"
katika Katy Perry.

428
00:20:52,820 --> 00:20:56,360
Hivyo basi hii inakuwa 0, na Gaga
mafanikio, ambayo ina maana kwamba Gaga ni

429
00:20:56,360 --> 00:20:57,310
pengine mwimbaji.

430
00:20:57,310 --> 00:20:58,560
Je, hiyo mantiki?

431
00:20:58,560 --> 00:21:00,700

432
00:21:00,700 --> 00:21:01,950
OK.

433
00:21:01,950 --> 00:21:04,160

434
00:21:04,160 --> 00:21:11,750
>> Hivyo kama nataka kufanya rasmi hii zaidi,
Mimi kweli anaweza kufanya mfano

435
00:21:11,750 --> 00:21:12,700
kwa maneno mengi.

436
00:21:12,700 --> 00:21:14,610
Basi hebu kusema kwamba nina kitu
kama, "mtoto, mimi

437
00:21:14,610 --> 00:21:16,030
juu ya moto, "au kitu.

438
00:21:16,030 --> 00:21:17,760
Hivyo ina maneno mengi.

439
00:21:17,760 --> 00:21:20,880
Na katika kesi hii, unaweza kuona
kwamba "mtoto" ni katika Gaga,

440
00:21:20,880 --> 00:21:21,710
lakini siyo katika Katy.

441
00:21:21,710 --> 00:21:24,940
Na "moto" ni katika Katy, lakini
siyo katika Gaga, sawa?

442
00:21:24,940 --> 00:21:27,200
Hivyo ni kupata trickier, sawa?

443
00:21:27,200 --> 00:21:31,440
Kwa sababu inaonekana kwamba wewe karibu
na tie kati ya mbili.

444
00:21:31,440 --> 00:21:36,980
>> Basi nini kufanya ni kudhani
independency kati ya maneno.

445
00:21:36,980 --> 00:21:41,210
Hivyo kimsingi nini maana ya ni kwamba
Mimi nina kuhesabu kile tu ni

446
00:21:41,210 --> 00:21:44,330
uwezekano wa kuona "mtoto," ni nini
uwezekano wa kuona "Mimi," na

447
00:21:44,330 --> 00:21:46,670
"Ni", na "juu ya," na "moto,"
wote tofauti.

448
00:21:46,670 --> 00:21:48,670
Basi mimi nina kuzidisha wao wote.

449
00:21:48,670 --> 00:21:52,420
Na mimi nina kuona nini ni uwezekano
ya kuona sentensi nzima.

450
00:21:52,420 --> 00:21:55,210
Mantiki?

451
00:21:55,210 --> 00:22:00,270
>> Hivyo kimsingi, kama mimi na neno moja tu,
nini nataka kupata ni ARG max,

452
00:22:00,270 --> 00:22:05,385
ambayo ina maana, ni nini darasa kwamba ni
kunipa uwezekano mkubwa?

453
00:22:05,385 --> 00:22:10,010
Kwa hiyo kile ni darasa kwamba ni kutoa
mimi uwezekano mkubwa kwa

454
00:22:10,010 --> 00:22:11,940
uwezekano wa darasa kutokana na neno.

455
00:22:11,940 --> 00:22:17,610
Hivyo katika kesi hii, Gaga kupewa "mtoto."
Au Katy kupewa "mtoto." Mantiki?

456
00:22:17,610 --> 00:22:21,040
>> Na tu kutoka Bayes, kwamba
equation kwamba mimi ilionyesha,

457
00:22:21,040 --> 00:22:24,780
sisi kujenga sehemu hii.

458
00:22:24,780 --> 00:22:28,750
Kitu pekee ni kwamba unaweza kuona kwamba
uwezekano wa neno kutokana na

459
00:22:28,750 --> 00:22:31,370
mabadiliko darasa kutegemea
juu ya darasa, sawa?

460
00:22:31,370 --> 00:22:34,260
idadi ya "mtoto" s kwamba mimi na
katika Gaga ni tofauti na Katy.

461
00:22:34,260 --> 00:22:37,640
uwezekano wa darasa pia
mabadiliko kwa sababu ni idadi tu ya

462
00:22:37,640 --> 00:22:39,740
ya nyimbo kila mmoja wao ana.

463
00:22:39,740 --> 00:22:43,980
>> Lakini uwezekano wa neno lenyewe
ni kwenda kuwa sawa kwa wote

464
00:22:43,980 --> 00:22:44,740
wasanii, sawa?

465
00:22:44,740 --> 00:22:47,150
Hivyo uwezekano wa neno ni
tu, ni nini uwezekano wa

466
00:22:47,150 --> 00:22:49,820
kuona kwamba neno katika
Lugha ya Kiingereza?

467
00:22:49,820 --> 00:22:51,420
Hivyo ni sawa kwa wote.

468
00:22:51,420 --> 00:22:55,790
Hivyo tangu hii ni mara kwa mara, tunaweza tu
tone hii na si huduma ya juu yake.

469
00:22:55,790 --> 00:23:00,230
Hivyo hii itakuwa kweli
equation sisi ni kuangalia kwa.

470
00:23:00,230 --> 00:23:03,360
>> Na kama mimi na maneno mengi, mimi nina
bado kwenda na kabla ya

471
00:23:03,360 --> 00:23:04,610
uwezekano hapa.

472
00:23:04,610 --> 00:23:06,980
Kitu pekee ni kwamba mimi nina kuzidisha
uwezekano wa

473
00:23:06,980 --> 00:23:08,490
maneno mengine yote.

474
00:23:08,490 --> 00:23:10,110
Hivyo mimi nina kuzidisha wao wote.

475
00:23:10,110 --> 00:23:12,610
Mantiki?

476
00:23:12,610 --> 00:23:18,440
Inaonekana weird lakini kimsingi ina maana,
mahesabu ya kabla ya darasa, na

477
00:23:18,440 --> 00:23:22,100
kisha kuongezeka kwa uwezekano wa kila
ya maneno kuwa katika darasa hilo.

478
00:23:22,100 --> 00:23:24,620

479
00:23:24,620 --> 00:23:29,150
>> Na unajua kwamba uwezekano wa
neno kutokana na darasa ni kwenda kuwa

480
00:23:29,150 --> 00:23:34,520
idadi ya nyakati unaweza kuona kwamba neno katika
kwamba darasa, kugawanyika kwa idadi ya

481
00:23:34,520 --> 00:23:37,020
maneno na kwa kuwa
darasa kwa ujumla.

482
00:23:37,020 --> 00:23:37,990
Mantiki?

483
00:23:37,990 --> 00:23:41,680
Ni jinsi "mtoto" ilikuwa 2 juu ya
idadi ya maneno kwamba

484
00:23:41,680 --> 00:23:43,020
Nilikuwa katika lyrics.

485
00:23:43,020 --> 00:23:45,130
Hivyo tu frequency.

486
00:23:45,130 --> 00:23:46,260
>> Lakini kuna jambo moja.

487
00:23:46,260 --> 00:23:51,250
Kumbuka jinsi mimi alikuwa kuonyesha kwamba
uwezekano wa "mtoto" kuwa lyrics

488
00:23:51,250 --> 00:23:56,350
kutoka Katy Perry alikuwa 0 kwa sababu tu Katy
Perry hakuwa na "mtoto" wakati wote?

489
00:23:56,350 --> 00:24:04,900
Lakini inaonekana kidogo kali tu
tu kusema kwamba lyrics hawezi kuwa kutoka

490
00:24:04,900 --> 00:24:10,040
msanii kwa sababu tu hawana
kwamba neno hasa wakati wowote.

491
00:24:10,040 --> 00:24:13,330
>> Hivyo unaweza kusema tu, vizuri, kama
hawana neno hili, mimi nina kwenda

492
00:24:13,330 --> 00:24:15,640
kukupa uwezekano chini,
lakini nina si tu kwenda

493
00:24:15,640 --> 00:24:17,420
kukupa 0 haki mbali.

494
00:24:17,420 --> 00:24:21,040
Kwa sababu labda ni kitu kama,
"Moto, moto, moto, moto," ambayo ni

495
00:24:21,040 --> 00:24:21,990
kabisa Katy Perry.

496
00:24:21,990 --> 00:24:26,060
Na kisha "mtoto," na huenda tu
0 haki mbali kwa sababu kulikuwa na mtu mmoja

497
00:24:26,060 --> 00:24:27,250
"Mtoto."

498
00:24:27,250 --> 00:24:31,440
>> Hivyo kimsingi nini cha kufanya ni kitu
aitwaye Laplace smoothing.

499
00:24:31,440 --> 00:24:36,260
Na hii ina maana tu kwamba mimi nina kutoa
baadhi uwezekano hata maneno

500
00:24:36,260 --> 00:24:37,850
ambazo hazipo.

501
00:24:37,850 --> 00:24:43,170
Hivyo nini mimi ni kwamba wakati mimi nina
kuhesabu, daima kuongeza 1 kwa

502
00:24:43,170 --> 00:24:44,180
numerator.

503
00:24:44,180 --> 00:24:48,060
Hivyo hata kama neno haipo, katika
kesi hii, kama hii ni 0, mimi bado nina

504
00:24:48,060 --> 00:24:51,250
kuhesabu hii kama 1 juu ya
jumla ya idadi ya maneno.

505
00:24:51,250 --> 00:24:55,060
Vinginevyo, mimi kupata jinsi maneno mengi
Mimi na mimi kuongeza 1.

506
00:24:55,060 --> 00:24:58,300
Hivyo mimi nina kuhesabu kwa hali zote mbili.

507
00:24:58,300 --> 00:25:00,430
Mantiki?

508
00:25:00,430 --> 00:25:03,060
>> Hivyo sasa hebu kufanya baadhi ya coding.

509
00:25:03,060 --> 00:25:06,440
Mimi nina kwenda na kufanya hivyo pretty haraka,
lakini ni muhimu tu kwamba

510
00:25:06,440 --> 00:25:08,600
guys kuelewa dhana.

511
00:25:08,600 --> 00:25:13,450
Hivyo kile sisi ni kujaribu kufanya
ni hasa kutekeleza hili

512
00:25:13,450 --> 00:25:14,330
jambo ambalo mimi tu alisema -

513
00:25:14,330 --> 00:25:19,110
Mimi nataka wewe kuweka lyrics kutoka
Lady Gaga na Katy Perry.

514
00:25:19,110 --> 00:25:22,980
Na mpango ni kwenda kuwa na uwezo wa
kusema kama haya lyrics mpya ni kutoka Gaga

515
00:25:22,980 --> 00:25:24,170
au Katy Perry.

516
00:25:24,170 --> 00:25:25,800
Mantiki?

517
00:25:25,800 --> 00:25:27,530
OK.

518
00:25:27,530 --> 00:25:30,710
>> Hivyo nina mpango huu mimi nina kwenda
kuwaita classify.py.

519
00:25:30,710 --> 00:25:31,970
Hivyo hii ni Python.

520
00:25:31,970 --> 00:25:34,210
Ni mpya lugha ya programu.

521
00:25:34,210 --> 00:25:38,020
Ni sawa sana katika baadhi
njia ya C na PHP.

522
00:25:38,020 --> 00:25:43,180
Ni sawa kwa sababu kama unataka
kujifunza Python baada ya kujua C, ni

523
00:25:43,180 --> 00:25:46,270
kweli si kwamba sehemu kubwa ya changamoto
kwa sababu tu Python ni rahisi sana

524
00:25:46,270 --> 00:25:47,520
kuliko C, kwanza ya yote.

525
00:25:47,520 --> 00:25:49,370
Na mambo mengi tayari
kutekelezwa kwa ajili yenu.

526
00:25:49,370 --> 00:25:56,820
Hivyo tu jinsi kama PHP ina kazi ambayo
aina orodha, au append kitu

527
00:25:56,820 --> 00:25:58,780
safu, au blah, blah, blah.

528
00:25:58,780 --> 00:26:00,690
Chatu ana wale wote pia.

529
00:26:00,690 --> 00:26:05,960
>> Hivyo mimi nina tu kwenda kueleza haraka
jinsi gani tunaweza kufanya uainishaji

530
00:26:05,960 --> 00:26:07,860
tatizo kwa hapa.

531
00:26:07,860 --> 00:26:13,230
Basi hebu kusema kwamba katika kesi hii, nina
lyrics kutoka Gaga na Katy Perry.

532
00:26:13,230 --> 00:26:21,880
njia ambayo mimi na wale lyrics ni kwamba
neno la kwanza la lyrics ni

533
00:26:21,880 --> 00:26:25,250
jina la msanii, na
wengine ni lyrics.

534
00:26:25,250 --> 00:26:29,470
Basi hebu kusema kwamba nina orodha hii katika
ambayo moja ya kwanza ni lyrics na Gaga.

535
00:26:29,470 --> 00:26:31,930
Hivyo hapa mimi juu ya haki ya kufuatilia.

536
00:26:31,930 --> 00:26:35,270
Na moja ijayo ni Katy, na
ina pia lyrics.

537
00:26:35,270 --> 00:26:38,040
>> Hivyo hii ni jinsi gani kutangaza
variable katika Python.

538
00:26:38,040 --> 00:26:40,200
Huna kwa kutoa aina data.

539
00:26:40,200 --> 00:26:43,150
Wewe tu kuandika "lyrics,"
aina ya kama katika PHP.

540
00:26:43,150 --> 00:26:44,890
Mantiki?

541
00:26:44,890 --> 00:26:47,770
>> Hivyo ni mambo ambayo mimi na nini
mahesabu ya kuwa na uwezo wa mahesabu ya

542
00:26:47,770 --> 00:26:49,360
probabilities?

543
00:26:49,360 --> 00:26:55,110
Mimi na kwa mahesabu ya "Priors"
ya kila mbalimbali

544
00:26:55,110 --> 00:26:56,710
madarasa ambayo mimi.

545
00:26:56,710 --> 00:27:06,680
Mimi na kwa mahesabu ya "posteriors,"
au pretty much probabilities ya

546
00:27:06,680 --> 00:27:12,150
kila ya maneno tofauti kwamba
Naweza kuwa na kwa kila msanii.

547
00:27:12,150 --> 00:27:17,210
Hivyo ndani ya Gaga, kwa mfano, mimi nina kwenda
kuwa na orodha ya mara ngapi mimi kuona

548
00:27:17,210 --> 00:27:19,250
kila ya maneno.

549
00:27:19,250 --> 00:27:20,760
Mantiki?

550
00:27:20,760 --> 00:27:25,370
>> Na hatimaye, mimi nina kwenda tu kuwa
orodha inayoitwa "maneno" kwamba ni kwenda tu

551
00:27:25,370 --> 00:27:29,780
kuwa na jinsi maneno mengi mimi
na kwa kila msanii.

552
00:27:29,780 --> 00:27:33,760
Hivyo kwa Gaga, kwa mfano, wakati mimi kuangalia
kwa lyrics, nilikuwa, nadhani, 24

553
00:27:33,760 --> 00:27:34,750
maneno katika jumla.

554
00:27:34,750 --> 00:27:38,970
Hivyo orodha hii ni kwenda tu kuwa na
Gaga 24, na Katy mwingine idadi.

555
00:27:38,970 --> 00:27:40,130
Mantiki?

556
00:27:40,130 --> 00:27:40,560
OK.

557
00:27:40,560 --> 00:27:42,530
>> Basi sasa, kwa kweli, hebu
kwenda coding.

558
00:27:42,530 --> 00:27:45,270
Hivyo katika Python, unaweza kweli
kurudi kundi la mbalimbali

559
00:27:45,270 --> 00:27:46,630
mambo kutoka kazi.

560
00:27:46,630 --> 00:27:50,810
Hivyo nina kwenda kujenga kazi hii
inayoitwa "masharti", ambayo ni kwenda

561
00:27:50,810 --> 00:27:53,890
kurudi yote ya mambo hayo,
"Priors," "probabilities," na

562
00:27:53,890 --> 00:28:05,690
"Maneno." Kwa hiyo, "masharti," na ni
kwenda kuwa wito katika "lyrics."

563
00:28:05,690 --> 00:28:11,510
>> Basi sasa mimi nataka wewe kweli
kuandika kazi hii.

564
00:28:11,510 --> 00:28:17,750
Hivyo njia kwamba naweza kuandika hii
kazi ni mimi tu kuelezwa hii

565
00:28:17,750 --> 00:28:20,620
kazi na "def." Hivyo mimi "def
masharti, "na ni kuchukua

566
00:28:20,620 --> 00:28:28,700
"Lyrics." Na jambo hili ni kwenda kufanya
ni, kwanza ya yote, nina Priors yangu

567
00:28:28,700 --> 00:28:31,030
kwamba mimi nataka mahesabu.

568
00:28:31,030 --> 00:28:34,330
>> Hivyo njia kwamba naweza kuwafanyia jambo hilo ni kujenga
kamusi katika Python, ambayo

569
00:28:34,330 --> 00:28:37,320
ni pretty much kitu kimoja kama hash
meza, au ni kama iterative

570
00:28:37,320 --> 00:28:40,480
safu katika PHP.

571
00:28:40,480 --> 00:28:44,150
Hii ni jinsi mimi kutangaza dictionary.

572
00:28:44,150 --> 00:28:53,580
Na kimsingi nini maana ya hii ni kwamba
Priors ya Gaga ni 0.5, kwa mfano, kama

573
00:28:53,580 --> 00:28:57,200
50% ya lyrics ni kutoka
Gaga, 50% ni kutoka Katy.

574
00:28:57,200 --> 00:28:58,450
Mantiki?

575
00:28:58,450 --> 00:29:00,680

576
00:29:00,680 --> 00:29:03,680
Hivyo nina kufikiri jinsi
mahesabu ya Priors.

577
00:29:03,680 --> 00:29:07,120
>> ndio pili kwamba mimi kufanya, pia,
ni probabilities na maneno.

578
00:29:07,120 --> 00:29:17,100
Hivyo probabilities ya Gaga ni orodha
ya probabilities wote kwamba mimi

579
00:29:17,100 --> 00:29:19,160
na kwa kila moja ya maneno kwa Gaga.

580
00:29:19,160 --> 00:29:23,880
Basi, ikiwa mimi kwenda probabilities ya Gaga
"Mtoto," kwa mfano, kutakuwa na kunipa

581
00:29:23,880 --> 00:29:28,750
kitu kama 2 zaidi ya 24 katika kesi hiyo.

582
00:29:28,750 --> 00:29:30,070
Mantiki?

583
00:29:30,070 --> 00:29:36,120
Basi, mimi kwenda na "probabilities" kwenda
"Gaga" ndoo ambayo ina orodha ya

584
00:29:36,120 --> 00:29:40,550
Maneno Gaga, basi mimi kwenda na "mtoto,"
na mimi kuona uwezekano.

585
00:29:40,550 --> 00:29:45,940
>> Na hatimaye nina hii
"Maneno" dictionary.

586
00:29:45,940 --> 00:29:53,620
Hivyo hapa, "probabilities." Na kisha
"Maneno." Basi, ikiwa mimi kufanya "maneno", "Gaga,"

587
00:29:53,620 --> 00:29:58,330
ni nini kinaenda kutokea ni kwamba ni
anaenda kunipa 24, kusema kwamba mimi

588
00:29:58,330 --> 00:30:01,990
na maneno 24 ndani ya lyrics kutoka Gaga.

589
00:30:01,990 --> 00:30:04,110
Hufanya akili?

590
00:30:04,110 --> 00:30:07,070
Hivyo hapa, "maneno" ni sawa na dah-dah-dah.

591
00:30:07,070 --> 00:30:07,620
OK

592
00:30:07,620 --> 00:30:12,210
>> Hivyo nini mimi kwenda kufanya ni mimi nina kwenda
iterate juu ya kila mmoja lyrics, hivyo

593
00:30:12,210 --> 00:30:14,490
kila ya masharti kwamba
Nina katika orodha.

594
00:30:14,490 --> 00:30:18,040
Na mimi nina kwenda kwa mahesabu ya mambo hayo
kwa kila mmoja wa wagombea.

595
00:30:18,040 --> 00:30:19,950
Hufanya akili?

596
00:30:19,950 --> 00:30:21,700
Hivyo nina kufanya kwa kitanzi.

597
00:30:21,700 --> 00:30:26,300
>> Hivyo katika Python nini siwezi kufanya ni "kwa ajili ya line
katika lyrics. "kitu kimoja kama

598
00:30:26,300 --> 00:30:28,000
"Kwa kila" taarifa katika PHP.

599
00:30:28,000 --> 00:30:33,420
Kumbuka jinsi ikiwa ni PHP mimi naweza
kusema "kwa kila lyrics kama

600
00:30:33,420 --> 00:30:35,220
line. "Hufanya akili?

601
00:30:35,220 --> 00:30:38,900
Hivyo mimi nina kuchukua kila wa mistari, katika hii
kesi, hii kamba na wa pili

602
00:30:38,900 --> 00:30:44,540
kamba hivyo kwa kila moja ya mistari nini mimi
kwenda kufanya ni mara ya kwanza, mimi nina kwenda kwa

603
00:30:44,540 --> 00:30:49,150
mgawanyiko mstari huu katika orodha ya
maneno kutengwa na nafasi.

604
00:30:49,150 --> 00:30:53,730
>> Hivyo jambo zuri kuhusu Python ni kwamba
unaweza tu Google kama "jinsi gani mimi

605
00:30:53,730 --> 00:30:58,220
mgawanyiko kamba katika maneno? "Na ni
kwenda kuwaambia jinsi ya kufanya hivyo.

606
00:30:58,220 --> 00:31:04,890
Na njia ya kufanya hivyo, ni tu "line
= Line.split () "na kimsingi ni

607
00:31:04,890 --> 00:31:08,640
kwenda kukupa orodha na
kila ya maneno hapa.

608
00:31:08,640 --> 00:31:09,620
Hufanya akili?

609
00:31:09,620 --> 00:31:15,870
Hivyo sasa kwamba mimi kwamba nataka kujua
ambao ni muimbaji wa wimbo huo.

610
00:31:15,870 --> 00:31:20,130
Na kwa kufanya hivyo mimi tu na kupata
hiki kwanza ya safu, sawa?

611
00:31:20,130 --> 00:31:26,390
Hivyo naweza kusema tu kwamba mimi "mwimbaji
= Line (0) "Hufanya akili?

612
00:31:26,390 --> 00:31:32,010
>> Na kisha mimi haja ya kufanya ni nini, ya kwanza ya
wote, mimi nina kwenda update wangapi

613
00:31:32,010 --> 00:31:36,130
maneno nina chini ya "Gaga." hivyo mimi nina tu
kwenda kwa mahesabu ya jinsi maneno mengi mimi

614
00:31:36,130 --> 00:31:38,690
na katika orodha hii, sawa?

615
00:31:38,690 --> 00:31:41,910
Kwa sababu hii ni jinsi maneno mengi mimi na
katika lyrics na mimi nina kwenda tu kwa

616
00:31:41,910 --> 00:31:44,120
kuongeza na "Gaga" safu.

617
00:31:44,120 --> 00:31:47,090
Je, hiyo mantiki?

618
00:31:47,090 --> 00:31:49,010
Wala kuzingatia sana juu ya syntax.

619
00:31:49,010 --> 00:31:50,430
Fikiria zaidi kuhusu dhana.

620
00:31:50,430 --> 00:31:52,400
Hiyo ni sehemu muhimu zaidi.

621
00:31:52,400 --> 00:31:52,720
OK.

622
00:31:52,720 --> 00:32:00,260
>> Basi nini siwezi kufanya hivyo ni kama "Gaga" ni
tayari katika orodha hiyo, hivyo "kama mwimbaji katika

623
00:32:00,260 --> 00:32:03,190
maneno "ambayo ina maana kwamba mimi tayari
na maneno kwa Gaga.

624
00:32:03,190 --> 00:32:06,640
Mimi nataka tu kuongeza nyongeza ya
maneno ya hiyo.

625
00:32:06,640 --> 00:32:15,810
Hivyo nini mimi ni "maneno (mwimbaji)
+ = Len (line) - 1 ".

626
00:32:15,810 --> 00:32:18,250
Na kisha naweza tu kufanya
urefu wa line.

627
00:32:18,250 --> 00:32:21,860
Mambo hivyo jinsi wengi mimi
na katika safu.

628
00:32:21,860 --> 00:32:27,060
Na mimi kufanya minus 1 kwa sababu tu
hiki kwanza ya safu ni

629
00:32:27,060 --> 00:32:29,180
mwimbaji na wale si lyrics.

630
00:32:29,180 --> 00:32:31,420
Hufanya akili?

631
00:32:31,420 --> 00:32:32,780
OK.

632
00:32:32,780 --> 00:32:35,820
>> "Else," maana yake ni kwamba mimi unataka kweli
kuingiza Gaga katika orodha.

633
00:32:35,820 --> 00:32:45,990
Hivyo mimi tu kufanya "maneno (mwimbaji)
= Len (line) - 1, "sorry.

634
00:32:45,990 --> 00:32:49,200
Hivyo tofauti kati ya wawili
mistari ni kwamba hii moja, haina

635
00:32:49,200 --> 00:32:51,080
halipo, hivyo mimi nina tu
initializing yake.

636
00:32:51,080 --> 00:32:53,820
Hii ni moja ya Mimi kwa kweli kuongeza.

637
00:32:53,820 --> 00:32:55,570
OK.

638
00:32:55,570 --> 00:32:59,480
Hiyo hii ilikuwa kuongeza maneno.

639
00:32:59,480 --> 00:33:03,040
>> Sasa nataka kuongeza Priors.

640
00:33:03,040 --> 00:33:05,480
Hivyo ni jinsi gani mimi mahesabu ya Priors?

641
00:33:05,480 --> 00:33:11,580
Priors inaweza kuwa mahesabu
na jinsi mara nyingi.

642
00:33:11,580 --> 00:33:15,340
Hivyo ni jinsi mara nyingi unaweza kuona kwamba mwimbaji
kati ya wote wa waimbaji kwamba

643
00:33:15,340 --> 00:33:16,380
na, sawa?

644
00:33:16,380 --> 00:33:18,810
Hivyo kwa Gaga na Katy Perry,
katika kesi hii, naona Gaga

645
00:33:18,810 --> 00:33:20,570
mara moja, Katy Perry mara moja.

646
00:33:20,570 --> 00:33:23,320
>> Hivyo kimsingi Priors kwa Gaga
na kwa Katy Perry ingekuwa

647
00:33:23,320 --> 00:33:24,390
tu kuwa moja, sawa?

648
00:33:24,390 --> 00:33:26,500
Wewe tu mara ngapi
Mimi naona msanii.

649
00:33:26,500 --> 00:33:28,740
Hivyo hii ni rahisi sana kwa mahesabu.

650
00:33:28,740 --> 00:33:34,100
Naweza tu kitu sawa kama kama "kama
mwimbaji katika Priors, "Mimi kwenda tu

651
00:33:34,100 --> 00:33:38,970
kuongeza 1 kwa Priors yao sanduku.

652
00:33:38,970 --> 00:33:51,000
Hivyo, "Priors (kuimba)" + = 1 "na kisha" mwingine "
Mimi nina kwenda kufanya "Priors (mwimbaji)

653
00:33:51,000 --> 00:33:55,000
= 1. "Hufanya akili?

654
00:33:55,000 --> 00:34:00,080
>> Hivyo kama haipo mimi tu ya kuweka
kama 1, vinginevyo mimi tu kuongeza 1.

655
00:34:00,080 --> 00:34:11,280
OK, hivyo sasa wote kwamba nina kushoto kufanya
pia kuongeza kila ya maneno ya

656
00:34:11,280 --> 00:34:12,290
probabilities.

657
00:34:12,290 --> 00:34:14,889
Hivyo nina kuhesabu ni mara ngapi
Mimi naona kila ya maneno.

658
00:34:14,889 --> 00:34:18,780
Hivyo mimi tu na kufanya mwingine
kwa kitanzi katika line.

659
00:34:18,780 --> 00:34:25,190
>> Kitu hivyo kwanza kwamba mimi nina kwenda kufanya ni
kuangalia kama mwimbaji tayari ina

660
00:34:25,190 --> 00:34:26,969
probabilities safu.

661
00:34:26,969 --> 00:34:31,739
Hivyo mimi nina kuangalia kama mwimbaji haina
na probabilities safu, mimi tu

662
00:34:31,739 --> 00:34:34,480
kwenda initialize moja kwa ajili yao.

663
00:34:34,480 --> 00:34:36,400
Siyo hata safu, sorry,
ni dictionary.

664
00:34:36,400 --> 00:34:43,080
Hivyo probabilities ya mwanamuziki ni kwenda
kuwa kamusi wazi, hivyo mimi nina

665
00:34:43,080 --> 00:34:45,830
tu initializing kamusi kwa ajili yake.

666
00:34:45,830 --> 00:34:46,820
OK?

667
00:34:46,820 --> 00:34:58,330
>> Na sasa mimi kweli anaweza kufanya kwa kitanzi
mahesabu ya kila ya maneno '

668
00:34:58,330 --> 00:35:00,604
probabilities.

669
00:35:00,604 --> 00:35:01,540
OK.

670
00:35:01,540 --> 00:35:04,160
Hivyo nini siwezi kufanya ni kwa kitanzi.

671
00:35:04,160 --> 00:35:06,590
Hivyo mimi nina tu kwenda iterate
juu ya safu.

672
00:35:06,590 --> 00:35:15,320
Hivyo njia kwamba naweza kufanya hivyo katika Python
ni "kwa ajili ya i katika mbalimbali." Kutoka 1

673
00:35:15,320 --> 00:35:19,200
kwa sababu Mimi nataka kuanza katika pili
hiki kwa sababu kwanza ni

674
00:35:19,200 --> 00:35:20,260
mwimbaji jina.

675
00:35:20,260 --> 00:35:24,990
Kwa hiyo kutokana na moja hadi
urefu wa line.

676
00:35:24,990 --> 00:35:29,760
Na wakati mimi mbalimbali ni kweli kwenda kutoka
kama hapa kutoka 1 kwa len ya

677
00:35:29,760 --> 00:35:30,740
line minus 1.

678
00:35:30,740 --> 00:35:33,810
Hivyo tayari gani kwamba jambo la kufanya
n minus 1 kwa arrays ambayo ni sana

679
00:35:33,810 --> 00:35:35,500
urahisi.

680
00:35:35,500 --> 00:35:37,850
Hufanya akili?

681
00:35:37,850 --> 00:35:42,770
>> Hivyo kwa kila moja ya haya, nini mimi kwenda kwa
kufanya ni, kama vile katika mtu mwingine,

682
00:35:42,770 --> 00:35:50,320
Mimi nina kwenda kuangalia kama neno katika hii
nafasi katika line tayari ni katika

683
00:35:50,320 --> 00:35:51,570
probabilities.

684
00:35:51,570 --> 00:35:53,400

685
00:35:53,400 --> 00:35:57,260
Na kisha kama nilivyosema hapa, probabilities
maneno, kama katika mimi kuweka

686
00:35:57,260 --> 00:35:58,400
"Probabilities (mwimbaji)".

687
00:35:58,400 --> 00:35:59,390
Na jina la mwimbaji.

688
00:35:59,390 --> 00:36:03,450
Hivyo kama ni tayari katika
"Probabilit (mwimbaji)", maana yake ni kwamba mimi

689
00:36:03,450 --> 00:36:11,960
unataka kuongeza 1 kwa hiyo, hivyo mimi nina kwenda kwa
kufanya "probabilities (mwimbaji)", na

690
00:36:11,960 --> 00:36:14,100
neno inaitwa "line (i)".

691
00:36:14,100 --> 00:36:22,630
Mimi nina kwenda kuongeza 1 na "mwingine" Mimi tu
kwenda initialize 1.

692
00:36:22,630 --> 00:36:23,880
"Line (i)".

693
00:36:23,880 --> 00:36:26,920

694
00:36:26,920 --> 00:36:28,420
Hufanya akili?

695
00:36:28,420 --> 00:36:30,180
>> Kwa hiyo, mimi mahesabu yote ya arrays.

696
00:36:30,180 --> 00:36:36,580
Kwa hiyo, sasa wote kwamba mimi kufanya kwa ajili ya
hii moja ni tu "kurudi Priors,

697
00:36:36,580 --> 00:36:43,230
probabilities na maneno. "Hebu
kuona kama kuna yoyote, OK.

698
00:36:43,230 --> 00:36:45,690
Inaonekana kila kitu ni kazi hadi sasa.

699
00:36:45,690 --> 00:36:46,900
Hivyo, kwamba inafanya hisia?

700
00:36:46,900 --> 00:36:47,750
Katika baadhi ya njia?

701
00:36:47,750 --> 00:36:49,280
OK.

702
00:36:49,280 --> 00:36:51,980
Basi sasa nina probabilities wote.

703
00:36:51,980 --> 00:36:55,100
Hivyo sasa kitu tu mimi wameondoka
ni tu na kwamba jambo

704
00:36:55,100 --> 00:36:58,650
mahesabu ya bidhaa ya yote
probabilities wakati mimi kupata lyrics.

705
00:36:58,650 --> 00:37:06,270
>> Basi hebu kusema kwamba mimi nataka sasa kuwaita
kazi hii "kuainisha ()" na

706
00:37:06,270 --> 00:37:08,880
kitu kazi ambayo inachukua
ni hoja tu.

707
00:37:08,880 --> 00:37:13,170
Hebu sema "Baby, mimi niko kwenye moto" na ni
kwenda kufikiri nini ni

708
00:37:13,170 --> 00:37:14,490
uwezekano kwamba hii ni Gaga?

709
00:37:14,490 --> 00:37:16,405
Ni uwezekano gani
kwamba hii ni Katie?

710
00:37:16,405 --> 00:37:19,690
Sauti nzuri?

711
00:37:19,690 --> 00:37:25,750
Hivyo mimi nina kwenda tu na kujenga
kazi mpya iitwayo "kuainisha ()" na

712
00:37:25,750 --> 00:37:29,180
ni kwenda kuchukua baadhi
lyrics pia.

713
00:37:29,180 --> 00:37:31,790

714
00:37:31,790 --> 00:37:36,160
Na badala ya lyrics mimi pia
na kutuma Priors,

715
00:37:36,160 --> 00:37:37,700
probabilities na maneno.

716
00:37:37,700 --> 00:37:44,000
Hivyo nina kwenda kwa kutuma lyrics, Priors,
probabilities, maneno.

717
00:37:44,000 --> 00:37:51,840
>> Hivyo hii ni kuchukua lyrics, Priors,
probabilities, maneno.

718
00:37:51,840 --> 00:37:53,530
Hiyo, ni nini ni nini?

719
00:37:53,530 --> 00:37:57,180
Ni kimsingi ni kwenda njia zote
wagombea inawezekana kwamba wewe

720
00:37:57,180 --> 00:37:58,510
na kama mwimbaji.

721
00:37:58,510 --> 00:37:59,425
Na ambapo ni wagombea hao?

722
00:37:59,425 --> 00:38:01,020
Wao uko katika Priors, sawa?

723
00:38:01,020 --> 00:38:02,710
Hivyo nina wale wote huko.

724
00:38:02,710 --> 00:38:07,870
Hivyo nina kwenda kuwa na kamusi
ya wagombea wote iwezekanavyo.

725
00:38:07,870 --> 00:38:14,220
Na kisha kwa kila mgombea katika
Priors, hivyo ina maana kwamba ni kwenda

726
00:38:14,220 --> 00:38:17,740
kuwa Gaga, Katie kama alikuwa
zaidi itakuwa zaidi.

727
00:38:17,740 --> 00:38:20,410
Mimi nina kwenda kuanza kuhesabu
uwezekano huu.

728
00:38:20,410 --> 00:38:28,310
uwezekano kama tuliona katika
PowerPoint ni mara kabla ya

729
00:38:28,310 --> 00:38:30,800
bidhaa ya kila
probabilities nyingine.

730
00:38:30,800 --> 00:38:32,520
>> Hivyo siwezi kufanya hivyo hapa.

731
00:38:32,520 --> 00:38:36,330
Naweza tu kufanya uwezekano ni
awali tu kabla ya.

732
00:38:36,330 --> 00:38:40,340
Hivyo Priors wa mgombea.

733
00:38:40,340 --> 00:38:40,870
Haki?

734
00:38:40,870 --> 00:38:45,360
Na sasa nina iterate juu ya yote
maneno ambayo nina katika lyrics kuwa

735
00:38:45,360 --> 00:38:48,820
uwezo wa kuongeza uwezekano
kwa kila mmoja wao, OK?

736
00:38:48,820 --> 00:38:57,900
Hivyo, "kwa neno katika lyrics" nini mimi kwenda
kufanya, kama neno ni katika

737
00:38:57,900 --> 00:39:01,640
"Probabilities (mgombea)", ambayo
ina maana kwamba ni neno

738
00:39:01,640 --> 00:39:03,640
mgombea ana katika lyrics yao -

739
00:39:03,640 --> 00:39:05,940
kwa mfano, "mtoto" kwa Gaga -

740
00:39:05,940 --> 00:39:11,710
nini mimi kwenda kufanya ni kwamba
uwezekano ni kwenda tele

741
00:39:11,710 --> 00:39:22,420
na 1 pamoja na probabilities ya
mgombea wa neno hilo.

742
00:39:22,420 --> 00:39:25,710
Na ni kuitwa "neno".

743
00:39:25,710 --> 00:39:32,440
Hii kugawanywa na idadi ya maneno
kwamba nina kwa mgombea huyo.

744
00:39:32,440 --> 00:39:37,450
jumla ya idadi ya maneno ambayo nina
kwa mwimbaji kwamba mimi nina kuangalia.

745
00:39:37,450 --> 00:39:40,290
>> "Else." maana ni neno jipya
hivyo Ningependa kuwa kama kwa mfano

746
00:39:40,290 --> 00:39:41,860
"Moto" kwa Lady Gaga.

747
00:39:41,860 --> 00:39:45,760
Kwa hiyo mimi nataka tu kufanya 1 juu ya
"Neno (mgombea)".

748
00:39:45,760 --> 00:39:47,710
Hivyo mimi si unataka kuweka muda huu hapa.

749
00:39:47,710 --> 00:39:50,010
>> Hivyo ni kwenda kwa kuwa kimsingi
kuiga na pasting hii.

750
00:39:50,010 --> 00:39:54,380

751
00:39:54,380 --> 00:39:56,000
Lakini mimi nina kwenda kufuta sehemu hii.

752
00:39:56,000 --> 00:39:57,610
Hivyo ni kwenda tu kuwa 1 juu ya hilo.

753
00:39:57,610 --> 00:40:00,900

754
00:40:00,900 --> 00:40:02,150
Sauti nzuri?

755
00:40:02,150 --> 00:40:03,980

756
00:40:03,980 --> 00:40:09,700
Na sasa mwishoni, mimi nina kwenda tu kwa
magazeti jina la mgombea na

757
00:40:09,700 --> 00:40:15,750
uwezekano kwamba una ya
kuwa S juu ya lyrics yao.

758
00:40:15,750 --> 00:40:16,200
Hufanya akili?

759
00:40:16,200 --> 00:40:18,390
Na mimi kwa kweli kufanya hata
haja kamusi hii.

760
00:40:18,390 --> 00:40:19,510
Hufanya akili?

761
00:40:19,510 --> 00:40:21,810
>> Kwa hiyo, hebu angalia kama hii kweli kazi.

762
00:40:21,810 --> 00:40:24,880
Basi, ikiwa mimi kukimbia hii, haikuwa kazi.

763
00:40:24,880 --> 00:40:26,130
Kusubiri moja ya pili.

764
00:40:26,130 --> 00:40:28,870

765
00:40:28,870 --> 00:40:31,720
"Maneno (mgombea)", "maneno (mgombea)",
kwamba

766
00:40:31,720 --> 00:40:33,750
jina la safu.

767
00:40:33,750 --> 00:40:41,435
OK Kwa hiyo, anasema kuna baadhi mdudu
kwa mgombea katika Priors.

768
00:40:41,435 --> 00:40:46,300

769
00:40:46,300 --> 00:40:48,760
Napenda tu chill kidogo.

770
00:40:48,760 --> 00:40:50,360
OK.

771
00:40:50,360 --> 00:40:51,305
Hebu jaribu.

772
00:40:51,305 --> 00:40:51,720
OK.

773
00:40:51,720 --> 00:40:58,710
>> Hivyo anatoa Katy Perry ana hili
uwezekano wa hili mara kwa mara 10 kwa

774
00:40:58,710 --> 00:41:02,200
minus 7, na Gaga ana hili
mara 10 kwa minus 6.

775
00:41:02,200 --> 00:41:05,610
Hivyo unaweza kuona inaonyesha kwamba Gaga
ina uwezekano ya juu.

776
00:41:05,610 --> 00:41:09,260
Kwa hiyo, "Baby, mimi nina on Fire" ni
pengine Gaga wimbo.

777
00:41:09,260 --> 00:41:10,580
Hufanya akili?

778
00:41:10,580 --> 00:41:12,030
Hivyo hii ni nini sisi alivyofanya.

779
00:41:12,030 --> 00:41:16,010
>> Kanuni hii ni kwenda kuwa posted online,
hivyo guys unaweza kuangalia ni nje.

780
00:41:16,010 --> 00:41:20,720
Labda kutumia baadhi ya ni kwa ajili ya kama unataka
kufanya mradi au kitu sawa.

781
00:41:20,720 --> 00:41:22,150
OK.

782
00:41:22,150 --> 00:41:25,930
Hii ilikuwa ni kuonyesha
nini computational

783
00:41:25,930 --> 00:41:27,230
isimu code inaonekana kama.

784
00:41:27,230 --> 00:41:33,040
Lakini sasa hebu kwenda zaidi
kiwango cha juu mambo ya ajabu.

785
00:41:33,040 --> 00:41:33,340
OK.

786
00:41:33,340 --> 00:41:35,150
>> Hivyo matatizo mengine mimi
alikuwa anazungumza juu ya -

787
00:41:35,150 --> 00:41:37,550
tatizo segmentation
ni ya kwanza ya yao.

788
00:41:37,550 --> 00:41:40,820
Hivyo kuwa hapa Japan.

789
00:41:40,820 --> 00:41:43,420
Na kisha unaweza kuona kwamba
hakuna nafasi.

790
00:41:43,420 --> 00:41:49,110
Hivyo hii ni kimsingi ina maana kwamba ni
juu ya kiti, sawa?

791
00:41:49,110 --> 00:41:50,550
Kusema Kijapani?

792
00:41:50,550 --> 00:41:52,840
Ni juu ya kiti, sawa?

793
00:41:52,840 --> 00:41:54,480
>> STUDENT: Mimi sijui nini
ja zaidi ya hapo ni.

794
00:41:54,480 --> 00:41:57,010
>> LUCAS Freitas: Ni [ANAZUNGUMZA Kijapani]

795
00:41:57,010 --> 00:41:57,950
OK.

796
00:41:57,950 --> 00:42:00,960
Hivyo kimsingi ina maana mwenyekiti wa juu.

797
00:42:00,960 --> 00:42:03,620
Hivyo kama wewe alikuwa na kuweka nafasi
itakuwa hapa.

798
00:42:03,620 --> 00:42:05,970
Na kisha una [? Ueda-san. ?]

799
00:42:05,970 --> 00:42:09,040
Ambayo kimsingi ina maana Mheshimiwa Ueda.

800
00:42:09,040 --> 00:42:13,180
Na unaweza kuona kwamba "Ueda" na una
nafasi na kisha "san." Hivyo unaweza kuona kwamba

801
00:42:13,180 --> 00:42:15,470
hapa "UE" ni kama kwa yenyewe.

802
00:42:15,470 --> 00:42:17,750
Na hapa ina tabia
karibu na hiyo.

803
00:42:17,750 --> 00:42:21,720
>> Hivyo si kama katika lugha hizo
wahusika maana neno ni hivyo

804
00:42:21,720 --> 00:42:23,980
tu kuweka mengi ya nafasi.

805
00:42:23,980 --> 00:42:25,500
Wahusika yanahusiana na kila mmoja.

806
00:42:25,500 --> 00:42:28,680
Na wanaweza kuwa pamoja
kama mbili, tatu, moja.

807
00:42:28,680 --> 00:42:34,520
Hivyo kweli na kujenga aina fulani
njia ya kuweka nafasi hizo.

808
00:42:34,520 --> 00:42:38,850
>> Na jambo hili ni kwamba wakati wowote, kupata
data kutoka lugha hizo Asia,

809
00:42:38,850 --> 00:42:40,580
kila kitu huja unsegmented.

810
00:42:40,580 --> 00:42:45,940
Kwa sababu hakuna mtu ambaye anaandika Kijapani
au Kichina anaandika na nafasi.

811
00:42:45,940 --> 00:42:48,200
Kila wewe ni kuandika Kichina,
Japan wewe andika tu kila kitu

812
00:42:48,200 --> 00:42:48,710
na hakuna nafasi.

813
00:42:48,710 --> 00:42:52,060
Haina hata mantiki
kuweka mazingira.

814
00:42:52,060 --> 00:42:57,960
Hivyo basi wakati kupata data kutoka, baadhi
Lugha Asia ya Mashariki, kama unataka

815
00:42:57,960 --> 00:43:00,760
kweli kufanya kitu na kwamba
una sehemu ya kwanza.

816
00:43:00,760 --> 00:43:05,130
>> Fikiria ya kufanya mfano wa
lyrics bila nafasi.

817
00:43:05,130 --> 00:43:07,950
Hivyo lyrics tu kwamba una
itakuwa hukumu, sawa?

818
00:43:07,950 --> 00:43:09,470
Kutengwa na vipindi.

819
00:43:09,470 --> 00:43:13,930
Lakini basi tu kuwa hukumu mapenzi
si kweli kusaidia juu ya kutoa taarifa

820
00:43:13,930 --> 00:43:17,760
nani wale lyrics ni kwa.

821
00:43:17,760 --> 00:43:18,120
Haki?

822
00:43:18,120 --> 00:43:20,010
Hivyo ni lazima unaweka nafasi ya kwanza.

823
00:43:20,010 --> 00:43:21,990
Hivyo jinsi gani unaweza kufanya hivyo?

824
00:43:21,990 --> 00:43:24,920
>> Hivyo basi huja wazo la lugha
mfano ambayo ni kitu kweli

825
00:43:24,920 --> 00:43:26,870
muhimu kwa computational
isimu.

826
00:43:26,870 --> 00:43:32,790
Hivyo mfano lugha kimsingi ni
meza ya probabilities kwamba inaonyesha

827
00:43:32,790 --> 00:43:36,260
Awali ya yote nini ni uwezekano
ya kuwa na neno katika lugha?

828
00:43:36,260 --> 00:43:39,590
Hivyo kuonyesha jinsi ya mara kwa mara neno ni.

829
00:43:39,590 --> 00:43:43,130
Na kisha pia kuonyesha uhusiano
kati ya maneno katika sentensi.

830
00:43:43,130 --> 00:43:51,500
>> Hivyo wazo kuu, kama mgeni alikuja
wewe na alisema adhabu

831
00:43:51,500 --> 00:43:55,600
ninyi, je, ni uwezekano kwamba, kwa
mfano, "hii ni dada yangu [? GTF"?]

832
00:43:55,600 --> 00:43:57,480
ni hukumu ya kwamba mtu alisema?

833
00:43:57,480 --> 00:44:00,380
Hivyo ni wazi baadhi ya sentensi ni
kawaida zaidi kuliko wengine.

834
00:44:00,380 --> 00:44:04,450
Kwa mfano, "asubuhi nzuri," au "nzuri
usiku, "au" hey huko, "ni zaidi ya

835
00:44:04,450 --> 00:44:08,260
kawaida zaidi kuliko hukumu nyingi za
kwamba tuna lugha ya Kiingereza.

836
00:44:08,260 --> 00:44:11,060
Hivyo kwa nini ni hukumu wale
mara kwa mara zaidi?

837
00:44:11,060 --> 00:44:14,060
>> Awali ya yote, ni kwa sababu una
maneno ambayo ni mara kwa mara.

838
00:44:14,060 --> 00:44:20,180
Hivyo, kwa mfano, kama wewe kusema, mbwa ni
kubwa, na mbwa ni mkubwa, wewe

839
00:44:20,180 --> 00:44:23,880
kawaida pengine kusikia mbwa ni kubwa
mara nyingi zaidi kwa sababu "kubwa" ni zaidi

840
00:44:23,880 --> 00:44:27,260
mara kwa mara katika lugha ya Kiingereza ya "mkubwa."
Kwa hiyo, moja ya

841
00:44:27,260 --> 00:44:30,100
mambo ni neno frequency.

842
00:44:30,100 --> 00:44:34,490
>> Jambo la pili ambayo ni kweli
muhimu ni tu

843
00:44:34,490 --> 00:44:35,490
utaratibu wa maneno.

844
00:44:35,490 --> 00:44:39,500
Kwa hiyo, ni kawaida kwa kusema "paka ni
ndani ya boksi. "lakini huna kawaida

845
00:44:39,500 --> 00:44:44,250
kuona katika "sanduku ndani ya ni paka." hivyo
unaweza kuona kwamba kuna baadhi ya umuhimu

846
00:44:44,250 --> 00:44:46,030
katika utaratibu wa maneno.

847
00:44:46,030 --> 00:44:50,160
Huwezi tu kusema kwamba hizo mbili
hukumu kuwa na uwezekano sawa

848
00:44:50,160 --> 00:44:53,010
kwa sababu tu wao na maneno yale yale.

849
00:44:53,010 --> 00:44:55,550
Wewe kweli kuwa na huduma ya
kuhusu utaratibu pia.

850
00:44:55,550 --> 00:44:57,650
Mantiki?

851
00:44:57,650 --> 00:44:59,490
>> Hivyo tunafanya nini?

852
00:44:59,490 --> 00:45:01,550
Basi nini mimi ili kujaribu kupata wewe?

853
00:45:01,550 --> 00:45:04,400
Mimi nina kujaribu kupata nini sisi
kuwaita mifano n-gram.

854
00:45:04,400 --> 00:45:09,095
Hivyo mifano n-gram kimsingi kudhani
kwamba kwa kila neno

855
00:45:09,095 --> 00:45:10,960
una katika hukumu.

856
00:45:10,960 --> 00:45:15,020
Ni uwezekano wa kuwa na kwamba
neno huko inategemea si tu juu ya

857
00:45:15,020 --> 00:45:18,395
mzunguko wa neno katika lugha,
lakini pia juu ya maneno ambayo

858
00:45:18,395 --> 00:45:19,860
ni jirani yake.

859
00:45:19,860 --> 00:45:25,810
>> Hivyo kwa mfano, kwa kawaida wakati unaweza kuona
kitu kama juu ya au wewe ni

860
00:45:25,810 --> 00:45:28,040
pengine ni kwenda kuona
noun baada ya yake, sawa?

861
00:45:28,040 --> 00:45:31,750
Kwa sababu wakati una preposition
kawaida inachukua noun baada ya yake.

862
00:45:31,750 --> 00:45:35,540
Au kama una verb kwamba ni elekezi
kawaida ni kwenda

863
00:45:35,540 --> 00:45:36,630
na noun maneno.

864
00:45:36,630 --> 00:45:38,780
Hivyo ni kwenda kuwa na noun
mahali fulani karibu yake.

865
00:45:38,780 --> 00:45:44,950
>> Kwa hiyo, kimsingi, kile yake ni kwamba
anaona uwezekano wa kuwa na

866
00:45:44,950 --> 00:45:47,960
maneno karibu na kila mmoja, wakati
wewe ni kuhesabu

867
00:45:47,960 --> 00:45:49,050
uwezekano wa adhabu.

868
00:45:49,050 --> 00:45:50,960
Na kwamba ni nini lugha
mfano ni kimsingi.

869
00:45:50,960 --> 00:45:54,620
Kusema tu nini uwezekano
ya kuwa na maalum

870
00:45:54,620 --> 00:45:57,120
hukumu katika lugha?

871
00:45:57,120 --> 00:45:59,110
Hivyo ni kwa nini kwamba muhimu, kimsingi?

872
00:45:59,110 --> 00:46:02,390
Na ya kwanza ya wote ni nini kwa
n-gram mfano, basi?

873
00:46:02,390 --> 00:46:08,850
>> Hivyo n-gram mfano ina maana kwamba
kila neno inategemea

874
00:46:08,850 --> 00:46:12,700
ijayo N minus 1 maneno.

875
00:46:12,700 --> 00:46:18,150
Kwa hiyo, kimsingi, ina maana kwamba kama mimi kuangalia,
kwa mfano, katika CS50 TF wakati

876
00:46:18,150 --> 00:46:21,500
Mimi nina kuhesabu uwezekano wa
hukumu, wewe utakuwa na kama "

877
00:46:21,500 --> 00:46:25,280
uwezekano wa kuwa na neno ""
mara uwezekano wa kuwa "

878
00:46:25,280 --> 00:46:31,720
CS50 "mara uwezekano wa kuwa na
"CS50 TF." Kwa hiyo, kimsingi, mimi kuhesabu

879
00:46:31,720 --> 00:46:35,720
kila njia ya kukaza mwendo yake.

880
00:46:35,720 --> 00:46:41,870
>> Na kisha kawaida wakati wewe ni kufanya hivyo,
kama katika mradi, kuweka N kuwa

881
00:46:41,870 --> 00:46:42,600
chini thamani.

882
00:46:42,600 --> 00:46:45,930
Hivyo, kwa kawaida na bigrams au trigrams.

883
00:46:45,930 --> 00:46:51,090
Ili tu kuhesabu maneno mawili, a
kundi la maneno mawili, au maneno tatu,

884
00:46:51,090 --> 00:46:52,620
tu kwa ajili ya masuala ya utendaji.

885
00:46:52,620 --> 00:46:56,395
Na pia kwa sababu labda kama una
kitu kama "CS50 TF." Wakati

886
00:46:56,395 --> 00:47:00,510
na "TF," ni muhimu sana kwamba
"CS50" ni karibu na hiyo, right?

887
00:47:00,510 --> 00:47:04,050
Mambo hayo mawili ni kawaida
karibu na kila mmoja.

888
00:47:04,050 --> 00:47:06,410
>> Kama unafikiri ya "TF," pengine ni
kwenda na nini

889
00:47:06,410 --> 00:47:07,890
darasa ni TF'ing kwa.

890
00:47:07,890 --> 00:47:11,330
Pia "" kwa kweli ni muhimu
kwa CS50 TF.

891
00:47:11,330 --> 00:47:14,570
Lakini kama una kitu kama "CS50
TF aliingia darasani na alitoa yao

892
00:47:14,570 --> 00:47:20,060
baadhi ya wanafunzi pipi. "" Candy "na" "
kuwa hakuna uhusiano kweli, haki?

893
00:47:20,060 --> 00:47:23,670
Wao uko hivyo mbali na kila mmoja kwamba
ni kweli haina jambo gani

894
00:47:23,670 --> 00:47:25,050
maneno na.

895
00:47:25,050 --> 00:47:31,210
>> Hivyo kwa kufanya bigram au trigram, ni
tu ina maana kwamba wewe ni kikwazo

896
00:47:31,210 --> 00:47:33,430
mwenyewe baadhi ya maneno
kwamba ni karibu.

897
00:47:33,430 --> 00:47:35,810
Mantiki?

898
00:47:35,810 --> 00:47:40,630
Hivyo wakati unataka kufanya segmentation,
kimsingi, nini unataka kufanya ni kuona

899
00:47:40,630 --> 00:47:44,850
ni njia zipi wote inawezekana kwamba
unaweza sehemu ya hukumu.

900
00:47:44,850 --> 00:47:49,090
>> Kama kwamba wewe kuona ni nini
uwezekano wa kila ya hukumu wale

901
00:47:49,090 --> 00:47:50,880
zilizopo katika lugha?

902
00:47:50,880 --> 00:47:53,410
Hivyo nini kufanya ni kama, vizuri, basi
mimi kujaribu kuweka nafasi hapa.

903
00:47:53,410 --> 00:47:55,570
Hivyo kuweka nafasi huko
na unaweza kuona nini ni

904
00:47:55,570 --> 00:47:57,590
uwezekano wa hukumu hiyo?

905
00:47:57,590 --> 00:48:00,240
Basi ni kama, OK, labda
kwamba alikuwa si nzuri.

906
00:48:00,240 --> 00:48:03,420
Basi, mimi kuweka nafasi huko na nafasi
huko, na mahesabu

907
00:48:03,420 --> 00:48:06,240
uwezekano sasa, na unaweza kuona kwamba
ni uwezekano mkubwa.

908
00:48:06,240 --> 00:48:12,160
>> Hivyo hii ni algorithm aitwaye TANGO
segmentation algorithm, ambayo ni

909
00:48:12,160 --> 00:48:14,990
kweli kitu ambacho itakuwa kweli
baridi kwa mradi huo, ambao

910
00:48:14,990 --> 00:48:20,860
kimsingi inachukua Nakala unsegmented ambayo
inaweza kuwa Japan au China au labda

911
00:48:20,860 --> 00:48:26,080
Kiingereza bila nafasi na anajaribu kuweka
nafasi kati ya maneno na haina

912
00:48:26,080 --> 00:48:29,120
kwamba kwa kutumia mfano lugha na
kujaribu kuona ni nini juu

913
00:48:29,120 --> 00:48:31,270
uwezekano unaweza kupata.

914
00:48:31,270 --> 00:48:32,230
OK.

915
00:48:32,230 --> 00:48:33,800
Hivyo hii ni segmentation.

916
00:48:33,800 --> 00:48:35,450
>> Sasa syntax.

917
00:48:35,450 --> 00:48:40,940
Hivyo, syntax ni kuwa kutumika kwa ajili ya
mambo mengi hivi sasa.

918
00:48:40,940 --> 00:48:44,880
Hivyo kwa Graph Search, kwa Siri kwa
pretty much aina yoyote ya asili

919
00:48:44,880 --> 00:48:46,490
usindikaji lugha una.

920
00:48:46,490 --> 00:48:49,140
Kwa hiyo kile ni muhimu
kuhusu mambo ya syntax?

921
00:48:49,140 --> 00:48:52,390
Kwa hiyo, hukumu kwa ujumla na
kile tunachokiita wapiga kura.

922
00:48:52,390 --> 00:48:57,080
Ambayo ni aina ya kama makundi ya maneno
kuwa na kazi katika hukumu.

923
00:48:57,080 --> 00:49:02,220
Na wanaweza si kweli kuwa
mbali na kila mmoja.

924
00:49:02,220 --> 00:49:07,380
>> Hivyo, kama mimi kusema, kwa mfano, "Lauren anapenda
Milo. "Najua kwamba" Lauren "ni

925
00:49:07,380 --> 00:49:10,180
Constituent na kisha "anapenda
Milo "ni pia mtu mwingine.

926
00:49:10,180 --> 00:49:16,860
Kwa sababu huwezi kusema kama "Lauren Milo
anapenda "kuwa na maana moja.

927
00:49:16,860 --> 00:49:18,020
Ni si kwenda kuwa na
maana moja.

928
00:49:18,020 --> 00:49:22,500
Au siwezi kusema kama "Milo Lauren
anapenda. "Si kila kitu ina sawa

929
00:49:22,500 --> 00:49:25,890
maana kufanya hivyo.

930
00:49:25,890 --> 00:49:31,940
>> Hivyo mambo mawili muhimu zaidi kuhusu
syntax ni aina lexical ambayo ni

931
00:49:31,940 --> 00:49:35,390
kimsingi kazi kwamba
na kwa maneno kwa wenyewe.

932
00:49:35,390 --> 00:49:39,180
Hivyo kuwa na kujua kwamba "Lauren"
na "Milo" ni nomino.

933
00:49:39,180 --> 00:49:41,040
"Upendo" ni kitenzi.

934
00:49:41,040 --> 00:49:45,660
Na jambo la pili muhimu ni
kwamba wao ni aina verbs.

935
00:49:45,660 --> 00:49:48,990
Hivyo unajua kuwa "anapenda Milo"
ni kweli maneno ya matusi.

936
00:49:48,990 --> 00:49:52,390
Hivyo wakati mimi kusema "Lauren," Najua kwamba
Lauren ni kufanya kitu fulani.

937
00:49:52,390 --> 00:49:53,620
Mwanamke anafanya nini?

938
00:49:53,620 --> 00:49:54,570
Yeye upendo Milo.

939
00:49:54,570 --> 00:49:56,440
Hivyo ni jambo zima.

940
00:49:56,440 --> 00:50:01,640
Lakini sehemu yake ni
noun na verb.

941
00:50:01,640 --> 00:50:04,210
Lakini pamoja, wao kufanya kifungu kitenzi.

942
00:50:04,210 --> 00:50:08,680
>> Hivyo, nini unaweza sisi kwa kweli kufanya na
computational isimu?

943
00:50:08,680 --> 00:50:13,810
Hivyo, kama mimi kuwa na kitu kwa mfano
"Marafiki wa Allison." Mimi naona kama mimi tu

944
00:50:13,810 --> 00:50:17,440
hakuwa mti Kiwango cha kisintaksia napenda kujua kwamba
"Marafiki" ni noun maneno ni

945
00:50:17,440 --> 00:50:21,480
noun na kisha "ya Allison" ni
prepositional maneno ambayo "ya" ni

946
00:50:21,480 --> 00:50:24,810
pendekezo na "Allison" ni jina.

947
00:50:24,810 --> 00:50:30,910
Nini mimi naweza kufanya ni kufundisha kompyuta yangu
kwamba wakati mimi na noun maneno moja na

948
00:50:30,910 --> 00:50:33,080
kisha maneno prepositional.

949
00:50:33,080 --> 00:50:39,020
Hivyo katika kesi hii, "marafiki" na kisha "ya
Milo "Najua kwamba hii ina maana kwamba

950
00:50:39,020 --> 00:50:43,110
NP2, wa pili, anamiliki NP1.

951
00:50:43,110 --> 00:50:47,680
>> Hivyo siwezi kujenga aina fulani ya uhusiano,
baadhi ya aina ya kazi kwa ajili yake.

952
00:50:47,680 --> 00:50:52,370
Hivyo wakati wowote naona muundo huu, ambayo
mechi hasa na marafiki wa "

953
00:50:52,370 --> 00:50:56,030
Allison, "Najua kwamba Allison
anamiliki marafiki.

954
00:50:56,030 --> 00:50:58,830
Hivyo marafiki ni kitu
kwamba Allison ana.

955
00:50:58,830 --> 00:50:59,610
Hufanya akili?

956
00:50:59,610 --> 00:51:01,770
Hivyo hii ni kimsingi nini
Graph Tafuta gani.

957
00:51:01,770 --> 00:51:04,360
Inasababisha sheria
kwa mambo mengi.

958
00:51:04,360 --> 00:51:08,190
Kwa hiyo, "marafiki wa Allison," "marafiki zangu
ambao wanaishi katika Cambridge, "" marafiki zangu

959
00:51:08,190 --> 00:51:12,970
wanaokwenda Harvard. "Ni inajenga sheria
kwa mambo hayo yote.

960
00:51:12,970 --> 00:51:14,930
>> Sasa tafsiri mashine.

961
00:51:14,930 --> 00:51:18,850
Hivyo, mashine ya tafsiri ni pia
kitu takwimu.

962
00:51:18,850 --> 00:51:21,340
Na kama kweli kujihusisha katika
isimu mahesabu, mengi ya

963
00:51:21,340 --> 00:51:23,580
mambo yako ni kwenda kuwa takwimu.

964
00:51:23,580 --> 00:51:26,670
Ili nilikuwa akifanya mfano pamoja
mengi ya probabilities kwamba mimi ni

965
00:51:26,670 --> 00:51:30,540
kuhesabu, na kisha kupata hii
idadi ndogo sana kwamba mwisho

966
00:51:30,540 --> 00:51:33,180
uwezekano, na kwamba ni nini
anatoa jibu.

967
00:51:33,180 --> 00:51:37,540
Tafsiri mashine pia hutumia
mfano takwimu.

968
00:51:37,540 --> 00:51:44,790
Na kama unataka kufikiri ya mashine
tafsiri katika rahisi iwezekanavyo

969
00:51:44,790 --> 00:51:48,970
njia, nini unaweza kufikiria ni
kutafsiri neno kwa neno, sawa?

970
00:51:48,970 --> 00:51:52,150
>> Wakati wewe ni kujifunza lugha kwa
mara ya kwanza, hiyo ni kawaida nini

971
00:51:52,150 --> 00:51:52,910
kufanya, sawa?

972
00:51:52,910 --> 00:51:57,050
Kama unataka kutafsiri hukumu
katika lugha yako kwa lugha

973
00:51:57,050 --> 00:52:00,060
wewe ni kujifunza, kwa kawaida kwanza,
kutafsiri kila ya maneno

974
00:52:00,060 --> 00:52:03,180
mmoja mmoja, na kisha kujaribu
kuweka maneno katika nafasi.

975
00:52:03,180 --> 00:52:07,100
>> Basi, ikiwa mimi alitaka kutafsiri hii,
[ANAZUNGUMZA KIRENO]

976
00:52:07,100 --> 00:52:10,430
ambayo ina maana "cat nyeupe mbio mbali."
Kama nilitaka kutafsiri kutoka

977
00:52:10,430 --> 00:52:13,650
Kireno Kiingereza, kile
inaweza kufanya ni, kwanza, mimi tu

978
00:52:13,650 --> 00:52:14,800
kutafsiri neno kwa neno.

979
00:52:14,800 --> 00:52:20,570
Kwa hiyo, "o" ni "," "Gato," "paka,"
"Branco," "nyeupe," na kisha "fugio" ni

980
00:52:20,570 --> 00:52:21,650
"Mbio mbali."

981
00:52:21,650 --> 00:52:26,130
>> Hivyo basi mimi na maneno yote hapa,
lakini siyo katika utaratibu.

982
00:52:26,130 --> 00:52:29,590
Ni kama "paka nyeupe wakakimbia"
ambayo ni ungrammatical.

983
00:52:29,590 --> 00:52:34,490
Kwa hiyo, basi naweza kuwa na hatua ya pili, ambayo
ni kwenda kuwa kutafuta bora

984
00:52:34,490 --> 00:52:36,610
nafasi kwa ajili ya kila ya maneno.

985
00:52:36,610 --> 00:52:40,240
Hivyo najua kwamba mimi kwa kweli unataka kuwa na
"Nyeupe paka" badala ya "cat nyeupe." Hivyo

986
00:52:40,240 --> 00:52:46,050
nini siwezi kufanya ni, njia ya naive
itakuwa kujenga wote

987
00:52:46,050 --> 00:52:49,720
permutations uwezekano wa
maneno, ya nafasi.

988
00:52:49,720 --> 00:52:53,300
Na kisha kuona ambayo moja ina
uwezekano mkubwa kwa mujibu

989
00:52:53,300 --> 00:52:54,970
kwa lugha mfano wangu.

990
00:52:54,970 --> 00:52:58,390
Na kisha wakati mimi kupata moja ambayo ina
uwezekano mkubwa yake, ambayo ni

991
00:52:58,390 --> 00:53:01,910
pengine "cat nyeupe akakimbia,"
kwamba tafsiri yangu.

992
00:53:01,910 --> 00:53:06,710
>> Na hii ni njia rahisi ya kueleza
jinsi mengi ya mashine tafsiri

993
00:53:06,710 --> 00:53:07,910
algorithms kazi.

994
00:53:07,910 --> 00:53:08,920
Je, hiyo mantiki?

995
00:53:08,920 --> 00:53:12,735
Hii pia ni kitu kweli kusisimua
kwamba wewe guys unaweza labda kuchunguza kwa

996
00:53:12,735 --> 00:53:13,901
mradi wa mwisho, yeah?

997
00:53:13,901 --> 00:53:15,549
>> Mwanafunzi: Naam, ninyi alisema ilikuwa
njia naive, hivyo nini

998
00:53:15,549 --> 00:53:17,200
mashirika yasiyo ya naive njia?

999
00:53:17,200 --> 00:53:18,400
>> LUCAS Freitas: njia zisizo za naive?

1000
00:53:18,400 --> 00:53:19,050
OK.

1001
00:53:19,050 --> 00:53:22,860
Hivyo jambo la kwanza kwamba ni mbaya kuhusu
njia hii ni kwamba mimi tu kutafsiriwa

1002
00:53:22,860 --> 00:53:24,330
maneno, neno kwa neno.

1003
00:53:24,330 --> 00:53:30,570
Lakini wakati mwingine una maneno ambayo
inaweza kuwa na tafsiri nyingi.

1004
00:53:30,570 --> 00:53:32,210
Mimi nina kwenda kujaribu kufikiri
ya kitu fulani.

1005
00:53:32,210 --> 00:53:37,270
Kwa mfano, "manga" kwa Kireno can
ama kuwa "guruta" au "sleeve." Hivyo

1006
00:53:37,270 --> 00:53:40,450
wakati wewe ni kujaribu kutafsiri neno
na neno, inaweza kuwa kutoa

1007
00:53:40,450 --> 00:53:42,050
kitu ambacho haina mantiki.

1008
00:53:42,050 --> 00:53:45,770
>> Hivyo kweli wanataka kuangalia wakati wote
tafsiri uwezekano wa

1009
00:53:45,770 --> 00:53:49,840
maneno na kuona, kwanza ya yote,
nini ni utaratibu.

1010
00:53:49,840 --> 00:53:52,000
Sisi walikuwa wanazungumza juu ya permutating
mambo?

1011
00:53:52,000 --> 00:53:54,150
Kuona maagizo yote iwezekanavyo na
kuchagua moja na ya juu

1012
00:53:54,150 --> 00:53:54,990
uwezekano?

1013
00:53:54,990 --> 00:53:57,860
Unaweza pia kuchagua inawezekana
tafsiri kwa kila

1014
00:53:57,860 --> 00:54:00,510
neno na kisha kuona -

1015
00:54:00,510 --> 00:54:01,950
pamoja na permutations -

1016
00:54:01,950 --> 00:54:03,710
ambayo moja ina uwezekano mkubwa.

1017
00:54:03,710 --> 00:54:08,590
>> Plus, unaweza pia kuangalia si
maneno tu lakini maneno.

1018
00:54:08,590 --> 00:54:11,700
hivyo unaweza kuchambua uhusiano kati ya
maneno na kisha kupata

1019
00:54:11,700 --> 00:54:13,210
bora ya tafsiri.

1020
00:54:13,210 --> 00:54:16,690
Pia kitu kingine, hivyo muhula hii
Mimi kwa kweli kufanya utafiti katika

1021
00:54:16,690 --> 00:54:19,430
Kichina-Kiingereza tafsiri mashine,
hivyo kutafsiri kutoka

1022
00:54:19,430 --> 00:54:20,940
Kichina katika lugha ya Kiingereza.

1023
00:54:20,940 --> 00:54:26,760
>> Na kitu sisi kufanya ni, badala ya kutumia
mfano takwimu, ambayo ni

1024
00:54:26,760 --> 00:54:30,570
kuona probabilities ya kuona
baadhi ya msimamo katika hukumu, mimi nina

1025
00:54:30,570 --> 00:54:35,360
kweli pia kuongeza baadhi ya syntax kwa yangu
mfano, akisema, oh, kama mimi kuona aina hii

1026
00:54:35,360 --> 00:54:39,420
ya ujenzi, hii ni nini nataka
mabadiliko hayo kwa wakati mimi kutafsiri.

1027
00:54:39,420 --> 00:54:43,880
Hivyo unaweza pia kuongeza baadhi ya aina ya
kipengele cha syntax kufanya

1028
00:54:43,880 --> 00:54:47,970
tafsiri ufanisi zaidi
na sahihi zaidi.

1029
00:54:47,970 --> 00:54:48,550
OK.

1030
00:54:48,550 --> 00:54:51,010
>> Hivyo jinsi gani unaweza kuanza, kama unataka
kufanya kitu katika computational

1031
00:54:51,010 --> 00:54:51,980
isimu?

1032
00:54:51,980 --> 00:54:54,560
>> Kwanza, unaweza kuchagua mradi
ambayo inahusisha lugha.

1033
00:54:54,560 --> 00:54:56,310
Hivyo, kuna wengi huko nje.

1034
00:54:56,310 --> 00:54:58,420
Kuna mambo mengi unaweza kufanya.

1035
00:54:58,420 --> 00:55:00,510
Na kisha unaweza kufikiria mfano
kwamba unaweza kutumia.

1036
00:55:00,510 --> 00:55:04,710
Kawaida kwamba maana yake ni mawazo ya
mawazo, kama kama, oh, wakati mimi nilikuwa

1037
00:55:04,710 --> 00:55:05,770
kama kufikiri ya maneno.

1038
00:55:05,770 --> 00:55:09,510
Mimi nilikuwa kama, vizuri, kama nataka kufikiri
nje ambaye aliandika hii, mimi pengine wanataka

1039
00:55:09,510 --> 00:55:15,400
kuangalia maneno mtu kutumika na
kuona ambaye anatumia neno kwamba mara nyingi sana.

1040
00:55:15,400 --> 00:55:18,470
Hivyo kujaribu kufanya mawazo na
jaribu kufikiria mifano.

1041
00:55:18,470 --> 00:55:21,395
Na kisha unaweza pia kutafuta online kwa
aina ya tatizo kwamba una,

1042
00:55:21,395 --> 00:55:24,260
na ni kwenda na kupendekeza
wewe mifano ya kwamba labda

1043
00:55:24,260 --> 00:55:26,560
inatokana kwamba kitu vizuri.

1044
00:55:26,560 --> 00:55:29,080
>> Na pia unaweza daima email yangu.

1045
00:55:29,080 --> 00:55:31,140
me@lfreitas.com.

1046
00:55:31,140 --> 00:55:34,940
Na naweza tu kujibu maswali yako.

1047
00:55:34,940 --> 00:55:38,600
Tunaweza hata wanaweza kukutana ili niweze
kutoa mapendekezo juu ya njia za

1048
00:55:38,600 --> 00:55:41,490
utekelezaji wa mradi wako.

1049
00:55:41,490 --> 00:55:45,610
Na mimi maana kama wewe kujihusisha na
isimu mahesabu, itakuja

1050
00:55:45,610 --> 00:55:46,790
kuwa kubwa.

1051
00:55:46,790 --> 00:55:48,370
Wewe ni kwenda kuona kuna
fursa nyingi mno.

1052
00:55:48,370 --> 00:55:52,060
Na sekta ya anataka kuajiri
hivyo mbaya kwa sababu ya hiyo.

1053
00:55:52,060 --> 00:55:54,720
Hivyo Natumaini guys starehe hii.

1054
00:55:54,720 --> 00:55:57,030
Kama wewe guys una maswali yoyote,
unaweza kuuliza mimi baada ya hii.

1055
00:55:57,030 --> 00:55:58,280
Lakini asante.

1056
00:55:58,280 --> 00:56:00,150