Idan kuna karanta wannan, babu shakka kun riga kun fara tafiya zuwa zurfin koyo. Idan kun kasance sababbi ga wannan batu, zurfin ilmantarwa shine ƙarawa wanda ke amfani da sifofi na musamman irin na kwakwalwa da ake kira hanyoyin sadarwa na wucin gadi don gina kwamfutoci irin na ɗan adam waɗanda ke magance al'amuran duniya.
Don taimakawa wajen haɓaka waɗannan ƙira, ƙirar fasaha kamar Google, Facebook, da Uber sun haɓaka tsari iri-iri don yanayin koyo mai zurfi na Python, yana mai da sauƙin fahimta, ƙirƙira, da horar da hanyoyin sadarwa iri-iri.
Tsarin ilmantarwa mai zurfi wani yanki ne na software da masana kimiyya da masana kimiyya ke amfani da su don ƙirƙira da horar da ƙirar ilmantarwa mai zurfi.
Manufar waɗannan tsare-tsare ita ce ba da damar mutane su horar da ƙirar su ba tare da fahimtar dabarun da ke baya ba zurfin ilmantarwa, hanyoyin sadarwa na jijiyoyi, da kuma koyon inji.
Ta hanyar babban tsarin mu'amalar shirye-shirye, waɗannan ginshiƙan suna ba da ginshiƙan ginin gini, horarwa, da tabbatar da ƙira.
Za mu dubi TensorFlow, Keras, Apache MXNet, Microsoft CNTK, da DeepLearing4j a matsayin madadin PyTorch, wanda aka yi amfani da shi sosai. tsarin ilmantarwa mai zurfi.
Menene Pytorch?
PyTorch kyauta ne, ɗakin karatu na koyo na inji wanda aka gina tare da ɗakin karatu na Torch Python.
Kungiyar Bincike ta AI ta Facebook ce ta kirkire ta kuma aka buga ta a matsayin dakin karatu kyauta kuma budaddiyar tushe a cikin Janairu 2016 tare da aikace-aikacen hangen nesa na kwamfuta, zurfin ilmantarwa, da sarrafa harshe na yanayi.
Yana da yaren shirye-shirye masu mahimmanci da Pythonic wanda ke goyan bayan lamba a matsayin abin ƙira, yana sauƙaƙe gyarawa, kuma ya dace da sauran mashahuran ɗakunan karatu na kimiyya, duk yayin da suke kasancewa masu inganci da ba da damar masu haɓaka kayan aiki kamar GPUs.
PyTorch ya girma cikin shahara a tsakanin masu binciken zurfafa ilmantarwa godiya ga mayar da hankali kan amfani da cikakken la'akarin aiki.
Ya ƙunshi tsarin bayanai na asali, Tensor, wanda shine tsararru mai girma dabam-dabam mai kama da Numpy arrays, wanda ke ba masu shirye-shirye damar ƙira mai rikitarwa cikin sauƙi. neural network.
Yana ƙara samun shahara a sassa na yanzu da kuma a cikin al'ummar ilimi saboda sassauƙansa, saurinsa, da sauƙin aiwatarwa, yana mai da shi ɗayan shahararrun kayan aikin ilmantarwa mai zurfi.
Fasalolin Maɓalli na Pytorch
- PyTorch shine Python-centric, ko "pythonic," saboda ana nufin shi don haɗawa mai zurfi tare da shirye-shiryen Python maimakon yin aiki azaman hanyar sadarwa zuwa ɗakin karatu da aka haɓaka a wani yare.
- Mai Sauƙi don Koyo - PyTorch yana bin tsari iri ɗaya da shirye-shiryen gargajiya kuma an tsara shi sosai, tare da masu haɓakawa koyaushe suna ƙoƙarin haɓaka shi. Don haka abu ne mai sauƙi don koyo ga masu shirye-shirye da waɗanda ba masu shirye-shirye ba.
- PyTorch na iya raba aikin lissafin akan CPU da yawa ko GPU cores ta amfani da damar daidaita bayanai. Ko da yake ana iya cimma daidaito irin wannan tare da wasu dabarun koyo na inji, PyTorch yana sa ya fi sauƙi.
- Gyara kuskure: Ana iya amfani da ɗaya daga cikin kayan aikin gyara kayan aikin Python da yawa (misali, Python's pdb da ipdb kayan aikin) ana iya amfani da su don gyara PyTorch.
- PyTorch yana goyan bayan faifan lissafi mai ƙarfi, wanda ke nuna cewa ana iya canza halayen hanyar sadarwa a lokacin aiki.
- PyTorch ya zo da nau'o'i na musamman da aka ƙirƙira, kamar su torchtext, torchvision, da torchaudio, wanda za a iya amfani dashi don magance fannoni daban-daban na zurfin ilmantarwa, kamar NLP, hangen nesa na kwamfuta, da sarrafa murya.
Ƙayyadaddun Pitorch
- Iyakantaccen saka idanu da musaya na gani: Yayin da TensorFlow ya haɗa da kayan aikin gani mai ƙarfi don ƙirƙirar jadawali samfurin (TensorBoard), a halin yanzu PyTorch ya rasa wannan fasalin. Sakamakon haka, masu haɓakawa na iya haɗawa zuwa TensorBoard a waje ko amfani da ɗayan yawancin Python da ke wanzuwa kayan aikin gani na bayanai.
- PyTorch ba ƙarshen-zuwa-ƙarshe ba ne injin inji dandalin ci gaba; yana tura aikace-aikace zuwa sabobin, wuraren aiki, da na'urorin hannu.
Don duk waɗannan dalilai, neman mafi kyawun madadin Pytorch zai zama shawara mai hikima.
Mafi mashahuri madadin Pytorch
Anan ne jerin mafi kyawun madadin Pytorch.
1. Tashin hankali
TensorFlow babban tsarin ilmantarwa ne mai zurfi, buɗaɗɗen tushen tsarin da Google ya ƙirƙira. Hakanan yana goyan bayan ma'auni injin inji. An ƙera TensorFlow tare da manyan ƙididdiga na ƙididdigewa, maimakon zurfin koyo.
Bugu da ƙari, ya tabbatar da cewa yana da ƙima sosai don ci gaban ilmantarwa mai zurfi kuma, don haka Google ya samar da shi kyauta. TensorFlow yana ɗaukar bayanai a cikin nau'ikan tsararraki masu girma dabam tare da mafi girma girma, da aka sani da tenors. Lokacin da ake mu'amala da ɗimbin ɗimbin bayanai, tsararraki masu girma dabam suna zuwa da taimako.
TensorFlow ya dogara ne akan jadawalin kwararar bayanai na kumburi. Saboda hanyar aiwatarwa tana ɗaukar nau'ikan jadawali, yana da sauƙin aiwatar da lambar TensorFlow akan tarin kwamfutoci yayin amfani da GPUs.
C#, Haskell, Julia, R, Ruby, Rust, da Scala suna cikin yarukan da jama'ar TensorFlow suka samar da tallafi don su. TensorFlow yana ba da fa'idar samun babban adadin wuraren shiga.
Baya ga harsuna, TensorFlow yana da manyan kayan aikin da ke haɗawa da shi ko kuma an gina su a kai.
Abũbuwan amfãni
- Yana da sauƙin amfani. Idan kun saba da Python, zai zama sauƙin ɗauka.
- Taimako daga al'umma. Ana inganta TensorFlow a zahiri kowace rana ta Google da sauran ƙwararrun ƙwararrun ƙungiyoyi.
- Ana iya amfani da TensorFlow Lite don aiwatar da ƙirar TensorFlow akan na'urorin hannu.
- Tensorboard kayan aiki ne don saka idanu da kuma gani data. Idan kuna son kallon ƙirar ƙirar ku mai zurfi a cikin aiki, wannan kyakkyawan kayan aiki ne don amfani.
- Tensorflow.js yana ba ku damar amfani da JavaScript don gudanar da ƙirar ilmantarwa mai zurfi na ainihin lokaci a cikin mai lilo.
disadvantages
- TensorFlow yana da tsari na musamman, yana sa ya fi wahalar ganowa da cire kurakurai.
- Babu goyon bayan OpenCL.
- TensorFlow baya samar da dama da yawa ga masu amfani da tsarin aiki na Windows. Yana buɗe yuwuwar iyawa ga masu amfani da Linux. Koyaya, masu amfani da Windows har yanzu suna iya zazzage TensorFlow ta amfani da saurin anaconda ko fakitin pip.
- TensorFlow yana faɗuwa a baya dangane da bayar da madaukai na alama don jeri mara iyaka. Yana da takamaiman amfani don jeri na musamman, yana mai da shi tsarin mai amfani. Sakamakon haka, ana ɗaukarsa azaman ƙaramin matakin API.
2. Karas
Keras ɗakin karatu ne mai zurfi na tushen Python, wanda ke bambanta shi da sauran tsarin ilmantarwa mai zurfi.
Yaren shirye-shirye ne mai girma wanda ke bayyana a neural network Bayanin API. Ana iya amfani da shi duka azaman hanyar sadarwa mai amfani kuma don haɓaka ƙarfin tsarin tsarin ilmantarwa mai zurfi wanda yake gudana akai.
Tsarin tsari kaɗan ne wanda ba shi da nauyi kuma mai sauƙin amfani. Don waɗannan dalilai, Keras wani yanki ne na ainihin API na TensorFlow. Ƙarshen gaba na Keras yana ba da damar yin saurin samfur na ƙirar hanyar sadarwa a cikin bincike.
API ɗin yana da sauƙi don fahimta da amfani, tare da ƙarin kari na ƙyale samfura don sauƙin canjawa wuri tsakanin tsarin.
Abũbuwan amfãni
- Keras API yana da sauƙi don amfani. API ɗin an tsara shi da kyau, daidaitaccen abu, kuma yana daidaitawa, yana haifar da ƙarin ƙwarewar mai amfani mai daɗi.
- An gina goyan bayan horarwar da aka rarraba da kuma daidaitawar GPU da yawa.
- Keras ƙwararren ɗan asalin Python ne wanda ke ba da sauƙi mai sauƙi zuwa cikakkiyar yanayin kimiyyar ilimin Python. Ana iya amfani da ƙirar Keras, alal misali, ta amfani da Python scikit-learn API.
- Keras ya haɗa da ma'aunin nauyi da aka riga aka horar don ƙirar koyo mai zurfi da yawa. Za mu iya amfani da waɗannan samfuran kai tsaye don yin tsinkaya ko cire fasali.
disadvantages
- Yana iya zama mai ban sha'awa mai ban sha'awa don samun ƙananan matakan baya akai-akai. Waɗannan matsalolin suna tasowa lokacin da muke ƙoƙarin yin ayyukan da Keras bai yi nufin cikawa ba.
- Idan aka kwatanta da na baya, yana iya zama sluggish akan GPUs kuma ya ɗauki tsawon lokaci don ƙididdigewa. A sakamakon haka, ƙila za mu lalata saurin don abokantaka na mai amfani.
- Idan aka kwatanta da sauran fakiti kamar sci-kit-learn, Keras iyawar sarrafa bayanai ba su da ban sha'awa.
3. Apache MX Net
Wani fitaccen Tsarin Ilimi mai zurfi MXNet. MXNet, wanda Gidauniyar Software ta Apache ta kirkira, tana goyan bayan yaruka iri-iri, gami da JavaScript, Python, da C++.
Sabis na Yanar Gizo na Amazon kuma yana goyan bayan MXNet a cikin haɓaka ƙirar ilmantarwa mai zurfi. Yana da matuƙar girma, yana ba da damar horar da samfuri cikin sauri, kuma yana dacewa da harsunan kwamfuta iri-iri.
Don haɓaka sauri da haɓaka aiki, MXNet yana ba ku damar haɗa alamomin da yarukan shirye-shirye masu mahimmanci. Ya dogara ne akan jadawali na dogaro mai ƙarfi wanda ke daidaita ayyukan alama da mahimmanci a cikin ainihin lokaci.
A saman wannan, Layer na inganta jadawali yana sa aiwatar da kisa na alama cikin sauri da tattalin arziki. MXNet ɗakin karatu ne mai ɗaukuwa kuma mara nauyi.
Ana ƙarfafa ta ta NVIDIA PascalTM GPUs kuma mai daidaitawa akan GPUs da nodes da yawa, yana ba ku damar horar da samfura cikin sauri.
Abũbuwan amfãni
- Yana goyan bayan GPUs kuma yana da yanayin GPU da yawa.
- Ingantacce, mai iya daidaitawa, da saurin walƙiya.
- Duk manyan dandamali suna kan jirgin.
- Hidimar samfurin abu ne mai sauƙi, kuma API ɗin yana da sauri.
- Scala, R, Python, C++, da JavaScript suna cikin harsunan shirye-shirye da ake tallafawa.
disadvantages
- MXNet yana da ƙarami Bude tushen al'umma fiye da TensorFlow.
- Haɓakawa, gyare-gyaren kwaro, da sauran haɓakawa suna ɗaukar lokaci mai tsawo don aiwatarwa saboda rashin gagarumin tallafin al'umma.
- MxNet, kodayake kamfanoni da yawa suna aiki da shi sosai a cikin masana'antar IT, ba a san shi sosai da Tensorflow ba.
4. Microsoft CNTK
Kayan aikin Fahimtar Microsoft (CNTK) tsarin buɗaɗɗen tushen tushen kasuwanci ne don rarraba zurfin ilmantarwa. Gabaɗaya ana amfani dashi don ƙirƙirar neural networks, amma kuma ana iya amfani da shi don koyon inji da ƙididdiga na fahimi.
Yana goyan bayan yaruka iri-iri kuma yana da sauƙin amfani akan gajimare. Saboda waɗannan halaye, CNTK ya dace da dacewa da aikace-aikacen AI iri-iri. Kodayake muna iya amfani da C++ don kiran ayyukanta, zaɓin da ya fi dacewa shine amfani da shirin Python.
Lokacin aiki akan kwamfutoci da yawa, Microsoft Cognitive Toolkit an gane shi don ba da kyakkyawan aiki da haɓaka fiye da kayan aikin kayan aiki kamar Theano ko TensorFlow.
Kayan aikin Fahimi na Microsoft yana goyan bayan nau'ikan jijiya na RNN da CNN, yana mai da shi dacewa da hoto, rubutun hannu, da ayyukan tantance magana.
Abũbuwan amfãni
- Mai sauƙi don haɗawa tare da Apache Spark, injin nazarin bayanai.
- Canjin girman CNTK ya sanya ya zama sanannen zaɓi a cikin kasuwancin da yawa. Akwai ingantattun abubuwa da yawa.
- Yana ba da kwanciyar hankali da kyakkyawan aiki.
- Yana aiki da kyau tare da Azure Cloud, duka biyun suna samun tallafi daga Microsoft.
- Amfani da albarkatu da gudanarwa suna da inganci.
disadvantages
- Idan aka kwatanta da Tensorflow, akwai ƙarancin tallafin al'umma.
- Hanyar koyo mai zurfi.
- Ba shi da allon gani da kuma tallafin ARM.
5. DeepLearning4j
Idan Java shine yaren shirye-shiryenku na farko, DeepLearning4j kyakkyawan tsari ne don amfani. Laburaren ilmantarwa ne da aka rarraba wanda ke da darajar kasuwanci da buɗaɗɗen tushe.
Duk manyan nau'ikan ƙirar hanyar sadarwa na jijiyoyi, kamar RNNs da CNNs, ana tallafawa. Deeplearning4j ɗakin karatu ne na Java da Scala don zurfin koyo.
Yana aiki da kyau tare da Hadoop da Apache Spark kuma. Deeplearning4j shine kyakkyawan madadin don tushen tushen zurfin ilmantarwa na tushen Java saboda yana goyan bayan GPUs.
Idan ya zo ga tsarin ilmantarwa mai zurfi na Eclipse Deeplearning4j, wasu daga cikin abubuwan da suka fi dacewa sun haɗa da horo iri ɗaya ta hanyar raguwar juzu'i, daidaita tsarin gine-ginen ƙananan sabis, da rarraba CPUs da GPUs.
Abũbuwan amfãni
- Yana da kyawawan takardu da taimakon al'umma.
- Haɗin Apache Spark abu ne mai sauƙi.
- Yana da ƙima kuma yana iya sarrafa ɗimbin bayanai.
disadvantages
- Idan aka kwatanta da Tensorflow da PyTorch, bai shahara ba.
- Java shine kawai yaren shirye-shirye da ake da shi.
Kammalawa
Zaɓin mafi kyawun tsarin ilmantarwa mai wahala aiki ne. Fiye da haka tun da akwai da yawa daga cikinsu, jerin suna girma kamar yadda ake bukata wucin gadi hankali bincike da aikace-aikacen koyon injin suna girma. Kowane tsarin yana da nasa tsarin fa'ida da rashin amfani.
Dole ne a yi la'akari da yawa, gami da tsaro, daidaitawa, da aiki. A cikin tsarin tsarin kasuwanci, dogaro ya zama mafi mahimmanci.
Idan kun fara farawa, Tensorflow wuri ne mai kyau don farawa. Zaɓi CNTK idan kuna haɓaka samfurin kasuwanci na tushen Windows. Idan kun fi son Java, yi amfani da DL4J.
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