Teburin Abubuwan Ciki[Boye][Nuna]
Af, dukkanmu muna sane da yadda fasahar koyon injin ta haɓaka cikin sauri a cikin shekaru da yawa da suka gabata. Koyon inji wani horo ne wanda ya jawo sha'awar kamfanoni da masana ilimi da sassa da yawa.
Saboda haka, zan tattauna wasu daga cikin manyan litattafai kan koyon injin da injiniyoyi ko sabon ɗan wasa ya kamata ya karanta a yau. Lallai duk kun yarda cewa karatun littafai ba daya bane da amfani da hankali.
Karatun littattafai yana taimaka wa tunaninmu ya gano sabbin abubuwa da yawa. Karatu shine koyo, bayan haka. Tambarin mai koyo yana da daɗi da yawa don samun. Za a ba da fifikon littattafan karatu mafi girma da ke cikin filin a cikin wannan labarin.
Littattafan karatu masu zuwa suna ba da gabatarwar gwaji da gaskiya ga babban filin AI kuma galibi ana amfani da su a cikin darussan jami'a kuma masana ilimi da injiniyoyi sun ba da shawarar.
Ko da kuna da ton na injin inji gogewa, ɗaukar ɗayan waɗannan littattafan na iya zama babbar hanya don gogewa. Bayan haka, koyo tsari ne mai ci gaba.
1. Koyon Injin Ga Cikakkun Mafari
Kuna so ku karanta koyan inji amma ba ku san yadda ake yi ba. Akwai mahimman ka'idoji da ƙididdiga masu mahimmanci da yawa waɗanda yakamata ku fahimta kafin fara balaguron balaguron ku zuwa koyan na'ura. Kuma wannan littafin ya cika wannan bukata!
Yana ba da cikakkun novices tare da babban matakin, zartarwa gabatarwa ga koyon inji. Littafin Machine Learning for Absolute Beginners yana ɗaya daga cikin mafi kyawun zaɓi ga duk wanda ke neman mafi sauƙaƙan bayanin koyan na'ura da ra'ayoyi masu alaƙa.
Algorithms na ml na littafin suna tare da taƙaitaccen bayani da misalai masu hoto don taimakawa masu karatu su fahimci duk abin da aka tattauna.
Batutuwan da ke cikin littafin
- Tushen neural networks
- Nazarin sakewa
- Injiniyan fasali
- Taronka
- Tabbatarwa ta giciye
- Dabarun goge bayanan
- Yanke Shawara
- Ƙirar ƙirar ƙira
2. Koyon Injin don Dummies
Koyon inji na iya zama ra'ayi mai ruɗani ga mutane na yau da kullun. Duk da haka, yana da ƙima ga waɗanda daga cikinmu masu ilimi.
Ba tare da ML ba, yana da wuya a sarrafa batutuwa kamar sakamakon binciken kan layi, tallace-tallace na ainihin lokaci akan shafukan yanar gizo, aiki da kai, ko ma tace spam (Ee!).
Sakamakon haka, wannan littafin yana ba ku gabatarwa mai sauƙi wanda zai taimaka muku ƙarin koyo game da duniyar koyan inji. Tare da taimakon Injin Learning For Dummies, za ku koyi yadda ake "magana" harsuna kamar Python da R, wanda zai ba ku damar horar da kwamfutoci don yin ƙirar ƙira da nazarin bayanai.
Bugu da ƙari, za ku koyi yadda ake amfani da Python's Anaconda da R Studio don haɓakawa a cikin R.
Batutuwan da ke cikin littafin
- Shirye-shiryen bayanai
- hanyoyin koyon inji
- Zagayowar koyon inji
- Koyon kulawa da rashin kulawa
- Tsarin koyar da injina
- Daure hanyoyin koyon inji zuwa sakamako
3. Littafin Koyon Injin Shafi Dari
Shin yana yiwuwa a rufe dukkan bangarorin koyo na inji a ƙasa da shafuka 100? Littafin Koyon Injin Shafi ɗari na Andriy Burkov ƙoƙari ne na yin hakan.
Littafin koyon injin yana da kyau rubuce kuma yana goyan bayan fitattun shugabannin tunani ciki har da Sujeet Varakhedi, Shugaban Injiniya a eBay, da Peter Norvig, Daraktan Bincike a Google.
Shi ne littafi mafi girma ga mafari a cikin koyon inji. Bayan karanta littafin sosai, za ku iya ginawa da fahimtar tsarin AI na yau da kullun, yin nasara a cikin hirar koyon injin, har ma da ƙaddamar da kamfanin ku na ML.
Koyaya, ba a yi nufin littafin ba don cikakken mafari a cikin koyan na'ura. Duba wani wuri idan kuna neman wani abu mafi mahimmanci.
Batutuwan da ke cikin littafin
- Anatomy na wani koyo algorithm
- Koyon kulawa da koyo mara kulawa
- Sanin Karatu
- Mahimman algorithms na Koyan Injin
- Bayanin hanyoyin sadarwa na Neural da zurfin koyo
4. Fahimtar Koyon Injin
An gabatar da gabatarwar tsari ga koyon injin a cikin littafin Understanding Machine Learning. Littafin ya zurfafa zurfi cikin ra'ayoyin tushe, tsarin lissafi, da abubuwan da suka samo asali na ilimin lissafi na koyan inji.
Ana gabatar da darussa masu yawa na koyon inji a cikin sauƙi ta hanyar koyon injin. An bayyana tushen tushen ilimin na'ura a cikin littafin, tare da abubuwan da suka samo asali na lissafi waɗanda ke juya waɗannan tushe zuwa algorithms masu amfani.
Littafin ya gabatar da mahimman bayanai kafin ya rufe batutuwa masu mahimmanci da yawa waɗanda littattafan karatu na farko ba su rufe su ba.
A cikin wannan akwai tattaunawa game da daidaituwar ra'ayi da kwanciyar hankali da haɗaɗɗen ƙididdigewa na ilmantarwa, da kuma mahimman ƙa'idodin algorithmic kamar stochastic. saukowa gradient, hanyoyin sadarwa na jijiyoyi, da tsarin ilmantarwa na fitarwa, da kuma sabbin ra'ayoyin ka'idoji masu tasowa kamar tsarin PAC-Bayes da iyakokin tushen matsawa. tsara don fara grads ko manyan digiri.
Batutuwan da ke cikin littafin
- Matsalolin lissafi na koyon inji
- Algorithms na ML
- Cibiyoyin Neural
- Hanyar PAC-Bayes
- Saukowar gradient na Stochastic
- Koyon fitarwa da aka tsara
5. Gabatarwa zuwa Koyan Injiniya tare da Python
Shin kai masanin kimiyyar bayanai ne na Python-savvy wanda ke son yin nazarin koyon injin? Mafi kyawun littafin don fara kasadar koyon injin ku da shi shine Gabatarwa zuwa Koyon Inji tare da Python: Jagora ga Masana Kimiyyar Bayanai.
Tare da taimakon littafin Gabatarwa zuwa Koyon Injiniya tare da Python: Jagora ga Masana Kimiyyar Bayanai, zaku gano dabaru iri-iri masu amfani don ƙirƙirar shirye-shiryen koyon injin na yau da kullun.
Za ku rufe kowane muhimmin mataki da ke cikin amfani da Python da kunshin Scikit-Learn don gina ingantaccen aikace-aikacen koyon injin.
Samun ƙwaƙƙarfan fahimtar matplotlib da dakunan karatu na NumPy zai sauƙaƙa koyo.
Batutuwan da ke cikin littafin
- Dabarun zamani don tweaking siga da ƙima samfurin
- Aikace-aikace da dabarun koyon inji
- dabarun koyo ta atomatik
- Dabaru don sarrafa bayanan rubutu
- Sarkar ƙirar ƙira da bututun rufewar aiki
- Wakilin bayanai bayan aiki
6. Koyon Injin hannu tare da Sci-kit koyo, Keras & Tensorflow
Daga cikin mafi ƙayyadaddun wallafe-wallafen kan ilimin kimiyyar bayanai da koyon injin, an cika shi da ilimi. Ana ba da shawarar cewa masana da novice su kara yin nazari game da wannan batu.
Ko da yake wannan littafin ya ƙunshi ɗan ƙaramin ka'idar, ana samun goyan bayansa da misalai masu ƙarfi, suna ba shi wuri a cikin jerin.
Wannan littafin ya ƙunshi batutuwa iri-iri, gami da scikit-koyi don ayyukan koyan inji da TensorFlow don ƙirƙira da horar da hanyoyin sadarwa.
Bayan karanta wannan littafin, muna tsammanin za ku fi dacewa ku sami damar zurfafa bincike a ciki zurfin ilmantarwa da magance matsalolin aiki.
Batutuwan da ke cikin littafin
- Yi nazarin yanayin koyan na'ura, musamman hanyoyin sadarwa na jijiyoyi
- Bibiyar aikin koyo na inji daga farkon zuwa ƙarshe ta amfani da Scikit-Learn.
- Bincika nau'ikan horarwa da yawa, kamar dabarun tarawa, dazuzzukan dazuzzuka, bishiyar yanke shawara, da injunan goyan baya.
- Ƙirƙiri da horar da hanyoyin sadarwa ta hanyar amfani da ɗakin karatu na TensorFlow.
- Yi la'akari da cibiyoyin sadarwa masu jujjuyawa, gidajen sauro na yau da kullun, da zurfin koyo na ƙarfafawa yayin bincike neural net kayayyaki.
- Koyi yadda ake aunawa da horar da hanyoyin sadarwa masu zurfi.
7. Koyon Injin Ga Masu Kutse
Ga ƙwararren masanin shirye-shirye masu sha'awar nazarin bayanai, an rubuta littafin Machine Learning for Hackers. Hackers ƙwararrun masanan lissafi ne a wannan mahallin.
Ga wanda ke da cikakkiyar fahimtar R, wannan littafi babban zaɓi ne domin yawancinsa ya dogara ne akan nazarin bayanai a cikin R. Bugu da ƙari kuma an rufe shi a cikin littafin shine yadda ake sarrafa bayanai ta amfani da ingantaccen R.
Haɗin abubuwan da suka dace suna jaddada ƙimar yin amfani da algorithms na koyon injin na iya zama mafi mahimmancin wurin siyar da littafin Machine Learning for Hackers.
Littafin ya ba da misalai da yawa na zahiri don sanya na'urar koyo ta zama mai sauƙi da sauri maimakon zurfafa cikin ka'idar lissafin sa.
Batutuwan da ke cikin littafin
- Ƙirƙiri mai rarraba Bayesian butulci wanda ke tantance abubuwan da ke cikin imel kawai don tantance ko spam ne.
- Hasashen adadin ra'ayoyin shafi na manyan gidajen yanar gizo 1,000 ta amfani da koma bayan layi
- Bincika hanyoyin ingantawa ta ƙoƙarin fashe madaidaicin sifar harafi.
8. Koyon Injin Python tare da Misalai
Wannan littafi, wanda ke taimaka muku fahimta da ƙirƙirar nau'ikan Learning Machine, zurfin koyo, da hanyoyin nazarin bayanai, wataƙila shine kaɗai wanda ya fi mayar da hankali kan Python kawai a matsayin yaren shirye-shirye.
Ya ƙunshi ɗakunan karatu masu ƙarfi da yawa don aiwatar da algorithms na Koyan Injin daban-daban, kamar Scikit-Learn. Sannan ana amfani da tsarin Tensor Flow don koya muku zurfin koyo.
A ƙarshe, yana nuna yawancin damar nazarin bayanai da za a iya samu ta amfani da na'ura da ilmantarwa mai zurfi.
Hakanan yana koya muku dabaru da yawa waɗanda za a iya amfani da su don haɓaka tasirin ƙirar da kuke ƙirƙira.
Batutuwan da ke cikin littafin
- Koyon Python da Koyan Injin: Jagorar Mafari
- Binciken saitin bayanan rukunin labarai guda 2 da gano imel na spam na Naive Bayes
- Amfani da SVMs, rarraba batutuwan labarun labarai Danna-ta hanyar tsinkaya ta amfani da algorithms dangane da bishiyoyi
- Hasashen ƙimar danna-ta hanyar amfani da koma bayan dabaru
- Amfani da regression algorithms don hasashen farashin hannun jari 'mafi girman ma'auni
9. Koyon Injin Python
Littafin Koyon Injin Python yana bayanin tushen koyan injin tare da mahimmancinsa a cikin yanki na dijital. Littafin koyon inji ne don masu farawa.
Bugu da kari an rufe shi a cikin littafin akwai fannonin koyon injina da yawa da aikace-aikace. Ka'idodin shirye-shiryen Python da yadda ake farawa da yaren shirye-shirye na kyauta da buɗaɗɗen tushe ana kuma rufe su a cikin littafin Koyon Injin Python.
Bayan kammala littafin koyon injin, zaku sami damar kafa adadin ayyukan koyo na inji ta amfani da Python coding.
Batutuwan da ke cikin littafin
- Tushen hankali na wucin gadi
- itace yanke shawara
- Tashin hankali
- Cibiyoyin sadarwa masu zurfi
- Tushen shirye-shiryen harshen Python
10. Koyon Injin: Ra'ayin Mai yiwuwa
Koyon Injin: Ra'ayin Mahimmanci littafi ne na koyon inji mai ban dariya wanda ke fasalta zane-zanen launi mai ban sha'awa da aiki, misalai na zahiri na duniya daga fannonin ilimi kamar ilimin halitta, hangen nesa na kwamfuta, robotics, da sarrafa rubutu.
Yana cike da litattafai na yau da kullun da kuma pseudocode don mahimman algorithms. Koyon Injin: Ra'ayi mai yiwuwa, ya bambanta da sauran wallafe-wallafen koyon inji waɗanda aka gabatar da su a cikin salon littafin dafa abinci da kuma bayyana hanyoyi daban-daban na haɓaka, yana mai da hankali kan tsari na tushen tsari mai ƙa'ida.
Yana ƙayyadaddun ƙirar ml ta amfani da zane-zane a sarari da fahimta. Dangane da haɗe-haɗe, hanya mai yuwuwa, wannan littafin yana ba da cikakkiyar gabatarwa mai zaman kanta ga fannin koyon injin.
Abubuwan da ke ciki duka biyu ne mai faɗi da zurfi, gami da mahimman abubuwan asali akan batutuwa kamar yuwuwar, haɓakawa, da algebra na layi, da kuma tattaunawa game da ci gaban zamani a cikin yanki kamar filayen bazuwar yanayi, daidaitawar L1, da zurfin koyo.
An rubuta littafin a cikin yare na yau da kullun, mai kusanci, mai ɗauke da lambar ƙirƙira don manyan mahimman algorithms.
Batutuwan da ke cikin littafin
- yiwuwa
- Deep learning
- L1 daidaitawa
- Optimization
- Tsarin rubutu
- Computer Vision aikace-aikace
- Robotics aikace-aikace
11. Abubuwan Ilmantarwa na Ƙididdiga
Don tsarin ra'ayi da kuma batutuwa iri-iri, wannan littafi na koyon na'ura galibi ana yarda da shi a fagen.
Ana iya amfani da wannan littafi a matsayin abin tunani ga duk wanda ke buƙatar gogewa akan batutuwa kamar hanyoyin sadarwa na jijiyoyi da dabarun gwaji da kuma gabatarwa mai sauƙi ga koyan na'ura.
Littafin yana matsawa mai karatu da ƙarfi don yin nasu gwaje-gwaje da bincike a kowane juzu'i, yana mai da shi mahimmanci don haɓaka iyawa da sha'awar da ake buƙata don samun ci gaba mai dacewa a cikin ƙarfin koyon injin ko aiki.
Yana da kayan aiki mai mahimmanci ga masu kididdiga da duk wanda ke sha'awar hakar bayanai a cikin kasuwanci ko kimiyya. Tabbatar cewa kun fahimci algebra na layi aƙalla kafin fara wannan littafin.
Batutuwan da ke cikin littafin
- Koyon kulawa (hasashen) zuwa ilmantarwa mara kulawa
- Cibiyoyin Neural
- Tallafa injunan vector
- Bishiyoyin Rarrabawa
- Ƙarfafa algorithms
12. Gane Samfura da Koyan Injin
Za a iya bincika duniyar ƙirar ƙirar ƙira da koyan injina sosai a cikin wannan littafin. Hanyar Bayesian don sanin ƙima an gabatar da ita a cikin wannan ɗaba'ar.
Bugu da ƙari, littafin yana nazarin batutuwa masu ƙalubale waɗanda ke buƙatar fahimtar aiki na multivariate, kimiyyar bayanai, da mahimman algebra na layi.
A kan koyan na'ura da yuwuwar, littafin tunani yana ba da surori tare da ci gaba da matsananciyar matakan rikitarwa dangane da abubuwan da ke faruwa a cikin bayanan bayanai. Ana bayar da misalai masu sauƙi kafin gabatarwa gabaɗaya don gane ƙirar ƙira.
Littafin yana ba da dabaru don ƙididdige ƙima, waɗanda ke ba da izinin kusantar da sauri a lokuta lokacin da ainihin mafita ba su da amfani. Babu wasu littattafan da ke amfani da ƙira na hoto don kwatanta rabon yiwuwar, amma yana yi.
Batutuwan da ke cikin littafin
- Hanyoyin Bayesian
- Algorithms na ƙima
- Sabbin samfura bisa kernels
- Gabatarwa ga ainihin ka'idar yiwuwa
- Gabatarwa ga sanin ƙirar ƙira da koyan na'ura
13. Tushen Koyon Injiniya daga Tattalin Arziki na Hasashen
Idan kun ƙware tushen ilimin na'ura kuma kuna son ci gaba zuwa nazarin bayanan tsinkaya, wannan shine littafin a gare ku !!! Ta hanyar nemo alamu daga ɗimbin bayanai, ana iya amfani da Koyon Inji don haɓaka ƙirar tsinkaya.
Wannan littafin yana nazarin aiwatar da amfani da ML Binciken Bayanan Hasashen a cikin zurfafa, gami da duka ka'idodin ka'idar da ainihin misalai.
Duk da cewa taken "Tabbas na Koyon Injin don Tattalin Arziki na Hasashen" na bakin ciki ne, wannan littafin zai zayyana tafiyar Hasashen Bayanan Hasashen daga bayanai zuwa haske zuwa ƙarshe.
Har ila yau, ya tattauna hanyoyin ilmantarwa na inji guda huɗu: ilmantarwa na tushen bayanai, ilmantarwa mai kama da juna, ilmantarwa na tushen yiwuwar, da kuma ilmantarwa na kuskure, kowanne tare da bayanin da ba na fasaha ba tare da tsarin lissafi da algorithms tare da misalai.
Batutuwan da aka rufe a cikin littafin
- Koyo na tushen bayanai
- Koyo na tushen kamanni
- Koyo na tushen yuwuwa
- Koyon tushen kuskure
14. Aiwatar Samfuran Hasashen
Aiwatar da Hasashen Hasashen yana nazarin gabaɗayan tsarin ƙirar ƙira, farawa da mahimman matakan sarrafa bayanai, rarrabuwar bayanai, da tushe na daidaita ƙirar ƙira.
Sa'an nan aikin ya gabatar da cikakkun bayanai game da nau'i-nau'i na al'ada da na baya-bayan nan da kuma hanyoyin rarrabawa, tare da mayar da hankali kan nunawa da warware ƙalubalen bayanai na ainihi.
Jagoran yana nuna duk nau'ikan tsarin ƙira tare da hannaye da yawa, misalan ainihin duniya, kuma kowane babi ya haɗa da cikakkiyar lambar R don kowane mataki na tsari.
Ana iya amfani da wannan ƙarar maƙasudi da yawa azaman gabatarwa ga ƙirar ƙira da duk tsarin ƙirar ƙira, azaman jagorar tunani ga masu sana'a, ko azaman rubutu don babban digiri na digiri ko digiri na biyu darussan tsinkayar ƙirar ƙira.
Batutuwan da ke cikin littafin
- Komawar fasaha
- Dabarar rarrabawa
- Complex ML algorithms
15. Koyon Injin: Fasaha da Kimiyya na Algorithms waɗanda ke ba da ma'anar bayanai
Idan kai matsakaita ne ko ƙwararre a cikin koyan na'ura kuma kuna son komawa "komawa ga tushe," wannan littafin na ku ne! Yana ba da cikakkiyar ƙima ga ƙaƙƙarfan ƙaƙƙarfan ƙwanƙwasa da zurfin Injin Learning yayin da ba ya rasa ganin ƙa'idodinsa na haɗin kai (cimmaci ne!).
Koyon Na'ura: Fasaha da Kimiyya na Algorithms sun haɗa da nazarce-nazarce da yawa na ƙara rikitarwa, da misalai da hotuna masu yawa (don kiyaye abubuwa masu ban sha'awa!).
Har ila yau, littafin ya ƙunshi nau'ikan ma'ana, geometric, da ƙididdiga, da kuma batutuwa masu rikitarwa da sabbin abubuwa kamar matrix factorization da bincike na ROC.
Batutuwan da ke cikin littafin
- Yana sauƙaƙa algorithms koyan inji
- Samfurin ma'ana
- Samfurin Geometric
- Misalin lissafi
- ROC bincike
16. Ma'adinan Bayanai: Kayan Aikin Koyon Injin & Dabaru
Yin amfani da hanyoyi daga nazarin tsarin bayanai, koyan inji, da ƙididdiga, dabarun haƙar ma'adinan bayanai suna ba mu damar samun alamu a cikin adadi mai yawa na bayanai.
Ya kamata ku sami littafin Data Mining: Practical Machine Learning Tools and Techniques idan kuna buƙatar nazarin dabarun haƙar ma'adinan bayanai musamman ko kuma kuyi shirin koyan koyon injin gabaɗaya.
Mafi kyawun littafi akan koyan inji yana mai da hankali sosai akan ɓangaren fasaha. Yana zurfafa zurfafa cikin dabarun fasahar koyon injin, da dabarun tattara bayanai da yin amfani da bayanai daban-daban da abubuwan da aka fitar don yanke hukunci.
Batutuwan da ke cikin littafin
- Tsarin layi
- Taronka
- Tsarin ƙididdiga
- Hasashen aiki
- Kwatanta hanyoyin haƙar ma'adinai
- Koyo na tushen misali
- Wakilin ilimi & gungu
- Dabarun hakar bayanai na gargajiya da na zamani
17. Python don Binciken Bayanai
Ikon tantance bayanan da aka yi amfani da su wajen koyan na'ura shine mafi mahimmancin fasaha da dole ne masanin kimiyyar bayanai ya mallaka. Kafin haɓaka samfurin ML wanda ke samar da ingantaccen hasashen, yawancin aikinku zai haɗa da sarrafawa, sarrafawa, tsaftacewa, da tantance bayanai.
Kuna buƙatar sanin yarukan shirye-shirye kamar Pandas, NumPy, Ipython, da sauransu don aiwatar da nazarin bayanai.
Idan kuna son yin aiki a kimiyyar bayanai ko koyon injin, dole ne ku sami ikon sarrafa bayanai.
Tabbas yakamata ku karanta littafin Python don Binciken Bayanai a wannan yanayin.
Batutuwan da ke cikin littafin
- Essential Karatuttukan Python
- Pandas na ci gaba
- Misalan Nazarin Bayanai
- Tsaftace bayanai da Shirye
- Hanyoyin Lissafi da Ƙididdiga
- Ƙididdiga da Ƙididdigar Ƙididdigar Ƙididdiga
18. Gudanar da Harshen Halitta tare da Python
Tushen tsarin koyon injin shine sarrafa harshe na halitta.
Littafin Tsarin Harshen Halitta tare da Python yana koya muku yadda ake amfani da NLTK, tarin abubuwan da ake so na Python da kayan aikin alama da ƙididdiga na sarrafa harshe na halitta don Ingilishi da NLP gabaɗaya.
Tsarin Harshen Halitta tare da littafin Python yana ba da ingantattun ayyukan yau da kullun na Python waɗanda ke nuna NLP a taƙaice, bayyane.
Masu karatu suna da damar samun bayanan bayanan da aka tsara don ma'amala da bayanan da ba a tsara su ba, tsarin rubutu-harshen, da sauran abubuwan da aka mayar da hankali kan NLP.
Batutuwan da ke cikin littafin
- Yaya harshen ɗan adam yake aiki?
- Tsarin bayanan harshe
- Kayan aikin Harshen Halitta (NLTK)
- Fassara da bincike na ma'ana
- Shahararrun bayanai na harshe
- Haɗa dabaru daga wucin gadi hankali da ilimin harshe
19. Shirye-shiryen Tattalin Arziki
The Programming Collective Intelligence by Toby Segaran, wanda ake la'akari a matsayin daya daga cikin mafi girma littattafai don fara fahimtar na'ura koyo, an rubuta a 2007, shekaru kafin kimiyyar bayanai da kuma na'ura koyo sun kai ga matsayin da suke a halin yanzu na jagorancin kwararru.
Littafin yana amfani da Python a matsayin hanya don yada ƙwarewarsa ga masu sauraronsa. Haɗin kai na Programming Collective Intelligence ya fi jagorar aiwatarwa ml fiye da gabatarwar koyan na'ura.
Littafin yana ba da bayanai kan haɓaka ingantaccen algorithms na ML don tattara bayanai daga aikace-aikace, tsara shirye-shirye don samun bayanai daga gidajen yanar gizo, da fitar da bayanan da aka tattara.
Kowane babi ya haɗa da ayyuka don faɗaɗa algorithm ɗin da aka tattauna da haɓaka amfaninsu.
Batutuwan da ke cikin littafin
- Bayesian tace
- Tallafa injunan vector
- Algorithms na injin bincike
- Hanyoyin yin tsinkaya
- Dabarun tace aikin haɗin gwiwa
- Matrix factorization mara kyau
- Haɓaka hankali don warware matsalar
- Hanyoyin gano ƙungiyoyi ko alamu
20. Zurfafa Ilmantarwa (Kimfuta Masu Daidaitawa da Jerin Koyon Inji)
Kamar yadda muka sani, zurfin ilmantarwa shine ingantaccen nau'in koyon injin wanda ke baiwa kwamfutoci damar koyo daga ayyukan da suka gabata da kuma adadi mai yawa na bayanai.
Yayin amfani da dabarun koyan na'ura, kuna buƙatar kuma ku kasance masu hulɗa tare da ƙa'idodin ilmantarwa mai zurfi. Wannan littafin, wanda ake ɗauka a matsayin Littafi Mai Tsarki na koyo mai zurfi, zai taimaka sosai a wannan yanayin.
Kwararru masu zurfin ilmantarwa guda uku sun rufe batutuwa masu sarkakiya wadanda ke cike da lissafi da kuma zurfafan samfura masu zurfi a cikin wannan littafi.
Samar da tushen lissafi da ra'ayi, aikin yana tattauna ra'ayoyi masu dacewa a cikin algebra na layi, ka'idar yuwuwa, ka'idar bayanai, ƙididdige ƙididdigewa, da koyan na'ura.
Yana nazarin aikace-aikace kamar sarrafa harshe na halitta, fahimtar magana, hangen nesa na kwamfuta, tsarin shawarwarin kan layi, bioinformatics, da wasannin bidiyo da kuma bayyana dabarun koyo mai zurfi waɗanda masu aikin masana'antu ke amfani da su, kamar hanyoyin sadarwa mai zurfi, daidaitawa, da haɓaka algorithms, hanyoyin sadarwa na juzu'i, da dabarun aiki. .
Batutuwan da ke cikin littafin
- Ƙididdigar Lissafi
- Binciken Ilimi mai zurfi
- Dabarun hangen nesa na Computer
- Zurfafa Feedforward Networks
- Haɓaka don Horar da Samfura masu zurfi
- Dabarun Aiki
- Binciken Ilimi mai zurfi
Kammalawa
An taƙaita manyan littattafan koyon inji guda 20 a cikin wannan jeri, waɗanda za ku iya amfani da su don ci gaba da koyon injin ta hanyar da kuke so.
Za ku iya haɓaka ƙaƙƙarfan tushe a cikin ƙwarewar koyon injin da ɗakin karatu wanda zaku iya amfani da shi sau da yawa yayin aiki a yankin idan kun karanta ire-iren waɗannan littattafan karatu.
Za a yi muku wahayi don ci gaba da koyo, samun kyawu, da samun tasiri koda kuwa kawai ku karanta littafi ɗaya.
Lokacin da kuka shirya kuma kun ƙware don haɓaka algorithms koyon injin ku, ku tuna cewa bayanai suna da mahimmanci ga nasarar aikin ku.
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