Uma uyinhloko yobunjiniyela besofthiwe, umcwaningi wesayensi yedatha, noma umthandi wezobuchwepheshe ngokujwayelekile kufanele wazi inkambu engaphansi ehamba phambili ye-Artificial Intelligence (AI) eyaziwa ngokuthi Ukufunda Ngomshini.
Kufanele futhi uqaphele izinhlelo zokusebenza eziningi ezihehayo ze-AI kusukela ekutholeni iphethini elula nokubonwa kwenkulumo kuya kubasizi ababonakalayo abahlanganisiwe abahlakaniphile. Lezi zinhlelo zokusebenza nokunye okuningi kwenziwa kwaba nokwenzeka ngemizamo yoNjiniyela Bokufunda Ngomshini.
Le ndatshana ixoxa ngokuthi obani laba Onjiniyela, benzani, nokuthi yimaphi amakhono adingekayo ukuze ube unjiniyela we-ML onekhono.
Benza Onjiniyela Bokufunda Ngomshini?
Ukufunda komshini (ML) Onjiniyela bahlanganisa amakhono ezibalo okuhlaziya nokuxazulula izinkinga nobuchwepheshe bokuhlela isofthiwe ukuze bakhe amasistimu e-AI ukuze axazulule izinkinga zomhlaba wangempela. Unjiniyela we-ML kudingeka ukuthi asebenze njengomhlaziyi wedatha ukuze asebenze futhi aguqule idatha ngokuya ngemfuneko enikeziwe futhi akhe, aqeqeshe, aqinisekise futhi ahlole ama-algorithms e-ML ngendlela yemodeli kudathasethi enikeziwe.
Onjiniyela abanjalo kungenzeka basebenze nenkampani emnyangweni wezobuchwepheshe, ngokuzimela njengomhleli noma njengomcwaningi ezinkingeni ze-ML ezisezingeni eliphezulu. Kunoma ikuphi, kunenani lezidingo zekhono okudingeka zihlangatshezwe ukuze ufaneleke njengoNjiniyela we-ML. Lawa makhono kuxoxwe ngawo kabanzi ngezansi.
5 Okufanele Ube Namakhono E-ML
1. Amathuba kanye Nokuhlaziywa Kwezibalo
Enye yezimfuneko ze-ML ihlanganisa ukuqonda okumaphakathi kwezihloko okuhlanganisa amathuba nezibalo. Lokhu kuyadingeka njengoba ama-algorithms we-ML namamodeli asekelwe kulezi zimiso zezibalo futhi awakwazi ukwakhiwa ngaphandle kwazo.
Amathuba abaluleke kakhulu uma kuziwa ekubhekaneni nokokufaka, okuphumayo, nokungaqiniseki komhlaba wangempela. Eminye imigomo yamathuba asetshenziswe ku-ML ihlanganisa amathuba anemibandela, umthetho we-Bayes, ukuba nokwenzeka, nokuzimela. Izibalo zisinikeza izilinganiso ezidingekayo zokwakha amamodeli e-ML okufaka phakathi incazelo, i-median, ukuhluka, ukusatshalaliswa (okufanayo, okujwayelekile, okubili, i-Poisson), nezindlela zokuhlaziya ezihlanganisa ukuhlolwa kwe-hypothesis.
2. Izisekelo Zokuhlela
Enye imfuneko ye-ML ukuba nokuqonda okuyisisekelo kokuhlela. Lokhu kufaka phakathi ukuqonda okulungile kwezakhiwo zedatha, okuhlanganisa izitaki, imigqa, amalungu afanayo anezinhlangothi eziningi, izihlahla, amagrafu, njll., nama-algorithms, okuhlanganisa ukusesha, ukuhlunga, ukulungiselelwa, ukuhlela okuguquguqukayo, njll.
Khetha ulimi lwakho
Mayelana izilimi zokuhlela, okungcono kakhulu ongakufunda nge-ML yiPython elandelwa yiJava. Lokhu kungenxa yokuthi iPython inokusekelwa okukhulu kwe-inthanethi ngokwekhodi etholakalayo, izinhlaka, nosizo lomphakathi.
Yazi i-IDE yakho
Isinyathelo esilandelayo ukuzijwayeza Imvelo Edidiyelwe Yokuthuthukiswa (IDE). Njengoba siphethe amanani amakhulu kakhulu edatha i-IDE yakho ayikwazi ukuba i-Command Line Interface (CLI) elula kunokuba ithuluzi elifana ne-Visual Studio Code noma Incwadi kaJupyter. NjengePython, i-Jupyter inokwesekwa okukhulu kwe-inthanethi futhi isetshenziswa abafundisi abaningi be-ML ngezinjongo zemfundo futhi.
Qonda Imitapo yolwazi
Imitapo yolwazi iqoqo lezinsiza okudingeka zingeniswe ohlelweni ngaphambi kokusetshenziswa. Kunenombolo yemitapo yolwazi ye-ML efana ne-TensorFlow, i-Keras, i-PyTorch, i-Pandas, i-Matplotlib, i-Numpy, njll. Kubalulekile ku-ML Engineer ukuthi ayiqonde kahle i-ML nemitapo yolwazi ephatha idatha ukuze enze izinhlelo zibe lula futhi zihlanganyele.
3. Ukumodelwa Kwedatha kanye Nokuhlola
Enye yezingxenye ezibalulekile ze-ML inqubo yokulinganisa isakhiwo esiyisisekelo sedathasethi ethile ukuze kutholwe amaphethini awusizo, okungukuthi, ukuhlobana, amaqoqo, ama-eigenvectors. Kuzodingeka futhi sibikezele izici zezimo zedatha ezihlanganisa ukuhlehla, ukuhlukanisa, nokutholwa okudidayo. Unjiniyela we-ML udinga ukuthi akwazi ukuhlola imodeli ethile esebenzisa imethrikhi yokunemba nesu.
4. Ukusebenzisa ama-Algorithms wokufunda ngomshini
Enye ingxenye ebalulekile ye-ML ukukwazi ukusebenzisa ama-algorithms e-ML. Kuhle ukuqaphela ukuthi ukwakha imodeli yakho akuvamile njengoba inani lamamodeli e-ML nokusetshenziswa sekukhona kakade kumalabhulali afana ne-Keras kanye ne-scikit-learn. Nokho, ukusebenzisa lawa mamodeli ngendlela ephumelela kakhulu nangokuhambisana nedathasethi kudinga kokubili ikhono nezinga elihle lokuqonda amamodeli e-ML ngokuvamile.
Unjiniyela we-ML kumele futhi aqaphele izinzuzo ezihambisanayo kanye nobubi bezindlela ezihlukene kanye nezinkinga ezingaba khona njengokugcwalisa ngokweqile, ukufaka ngaphansi, ukuchema, kanye nezinkinga zokuhlukahluka.
5. Yakha Neural Networks
I-Neural Networks (NNs) iyingxenye yenkambu engaphansi ye-ML eyaziwa ngokuthi Ukufunda Okujulile futhi iyisidingo esinwetshiwe uma kuziwa kumakhono abalulekile e-ML. Nokho, ekusebenziseni okungokoqobo kwe-ML, sidinga ukuqonda okuthile kwama-NN ukuze sakhe amamodeli anamandla ezinhlelo zethu ze-AI.
I-NN isebenzisa izendlalelo nama-neurons ukuze idale amamodeli e-ML anamandla. Unjiniyela we-ML kufanele akwazi ukwakha, aqeqeshe, aqinisekise futhi ahlole ama-NN.
Isiphetho
Manje kufanele uqonde kahle ukuthi ubani Ukufunda komshini Onjiniyela bangonjiniyela, benzani, nokuthi yimaphi amakhono adingekayo ukuze uqale uhambo lwakho. Udinga ukwazi kahle amathuba, ukuhlaziya izibalo, ukuhlela, ukumodela idatha, izinhlelo zokusebenza ze-algorithms, kanye ukwakha amanethiwekhi e-neural ukwakha izixazululo ezinamandla ze-AI ne-ML.
Sazise kumazwana uma i-athikili ibe usizo futhi ucabanga ukuthi iliphi ikhono elibaluleke kakhulu lokuba unjiniyela we-ML ochwepheshile.
shiya impendulo