Ukufunda kwenguxa

ukufundwa kwemikholezima eziphucula ngenhleleleko isebenzisa ubungcweti

Ukufunda kwenguxa yibizo elibhekisela ekuxazululweni kwezinkinga ebezizovimba abahlelelisi ukuba bakwazi ukuthuthukisa imikholezima, kepha kunalokho lezo zinkinga zixazululwa ngokulekelela izinguxa ukuba "zivubukule" imikholezima yazo,[1] ngaphandle kokutshelwa ngokuqondile ukuba zenzeni yinona yimiphi imikholezima evela kumuntu. Kamuva, amaxhoxho weNzwa wokuzakhela aphehlwayo akwazile ukuqoqoda imiphumela yezindlela ezandulele.[2][3] Izinsondelo zokufunda kwenguxa ziye zasetshenziswa ezinongweni zolimi ezinkulu, umbono wesiCikizi, ukuhlonza iphimbo, ukuhlunga incwazuba, kwezolimo nakwezokwelapha, lapho kubiza imali eningi ukuthuthukisa imikholezima ezoqhogoya imisebenzi eyisidingo.[4][5]


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Iziseko zomchazazibalo wokufunda kwenguxa zitholakala ngezindlelasu zokuhlelelisa komchazazibalo. Ukumonyula imininingo omunye umkhakha ohlobene, ogxile kwisihlaziyo semininingo esihlwayayo esisebenzisa ukufundwa okungaqondisiwe.

Imithombo hlela

  1. Ethem Alpaydin (2020). Introduction to Machine Learning (Fourth ed.). MIT. pp. xix, 1–3, 13–18. ISBN 978-0262043793.
  2. "What is Machine Learning? | IBM". www.ibm.com (in i-English). Kulandwe ngomhlaka 2023-06-27.
  3. Zhou, Victor (2019-12-20). "Machine Learning for Beginners: An Introduction to Neural Networks". Medium (in i-English). Archived from the original on 2022-03-09. Kulandwe ngomhlaka 2021-08-15. Unknown parameter |url-status= ignored (help)
  4. Hu, Junyan; Niu, Hanlin; Carrasco, Joaquin; Lennox, Barry; Arvin, Farshad (2020). "Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning". IEEE Transactions on Vehicular Technology 69 (12): 14413–14423. doi:10.1109/tvt.2020.3034800. ISSN 0018-9545. http://dx.doi.org/10.1109/tvt.2020.3034800. Retrieved 2023-04-16. 
  5. Yoosefzadeh-Najafabadi, Mohsen; Hugh, Earl; Tulpan, Dan; Sulik, John; Eskandari, Milad (2021). "Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in Soybean?". Front. Plant Sci. 11: 624273. doi:10.3389/fpls.2020.624273. PMC 7835636. PMID 33510761. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=7835636.