<prompt> Hlalosa phapang lipakeng tsa mochini le thuto e tebilengnan  <response>: Instruction in English: Describe the differences between machine and deep learning . Response in English: Machine learning and deep learning are both subfields of artificial intelligence, with deep learning being a subset of machine learning. Both technologies enable computers to learn from data and improve their performance over time. However, there are some fundamental differences between the two.Machine learning algorithms are designed to learn from data and make predictions or decisions based on that data. These algorithms can be divided into three main categories - supervised, unsupervised, and reinforcement learning- and they are often used for tasks such as classification, regression, clustering, and anomaly detection. Machine learning algorithms require feature extraction where relevant features that represent the data in the best possible way are selected and fed to the machine learning models.Deep learning, on the other hand, is a type of machine learning that uses neural networks with multiple layers. These layers are capable of learning features automatically from the data without the need for manual feature extraction. Deep learning algorithms can handle large amounts of data and are able to learn complex patterns or relationships, making them suitable for tasks such as image and speech recognition, natural language processing, and computer vision.In summary, the main difference between machine learning and deep learning is the approach to learning from data. Machine learning algorithms often require human intervention to select relevant features, while deep learning algorithms are designed to automatically learn features from raw data. Deep learning models can handle more complex data and tasks, but often require larger amounts of data and computational power to train effectively. . Response in Sesotho: Ho ithuta ka mochini le ho ithuta ka botebo ke likaroloana tsa bohlale ba maiketsetso, me thuto e tebileng e le karoloana ea ho ithuta ka mochini. Theknoloji ka bobeli e thusa likhomphutha ho ithuta ho tsoa ho data le ho ntlafatsa tsebetso ea tsona ha nako e ntse e ea. Leha ho le joalo, ho na le phapang e itseng ea motheo pakeng tsa lintho tsena tse peli. Li-algorithms tsa ho ithuta ka mochini li etselitsoe ho ithuta ho tsoa ho data le ho etsa likhakanyo kapa liqeto ho latela data eo. Litharollo tsena li ka aroloa ka likarolo tse tharo tse kholo - thuto e hlokometsoeng, e sa hlokomeloe, le e matlafatsoang - me hangata e sebelisoa bakeng sa mesebetsi e kang ho arola, ho fokotseha, ho kopanya le ho lemoha ka mokhoa o sa tloaelehang. Litaolo tsa ho ithuta ka mochini li hloka ho ntšoa ha likarolo moo likarolo tse amehang tse emelang datha ka tsela e nepahetseng li khethoang le ho feptjoa mefuteng ea ho ithuta ea mochini. Ho ithuta ho tebileng, ka lehlakoreng le leng, ke mofuta oa ho ithuta ka mochini o sebelisang marang-rang a neural a nang le mekhahlelo e mengata. Likarolo tsena li khona ho ithuta likarolo ka bo eona ho tsoa ho data ntle le tlhoko ea ho ntšoa ha likarolo tsa letsoho. Li-algorithms tse tebileng tsa ho ithuta li ka sebetsana le lintlha tse ngata me li khona ho ithuta mekhoa e rarahaneng kapa likamano, ho etsa hore li tšoanelehe bakeng sa mesebetsi e kang ho lemoha litšoantšo le puo, ho sebetsana le puo ea tlhaho, le pono ea khomphieutha. Ka kakaretso, phapang e kholo lipakeng tsa ho ithuta ka mochini le thuto e tebileng ke mokhoa oa ho ithuta ho tsoa ho data. Mekhoa ea ho ithuta ka mochini hangata e hloka hore motho a kenelle ho khetha likarolo tse amehang, athe li-algorithms tse tebileng tsa ho ithuta li etselitsoe ho ithuta likarolo tsa data tse tala. Mehlala ea ho ithuta e tebileng e ka sebetsana le lintlha le mesebetsi e rarahaneng, empa hangata e hloka lintlha tse kholoanyane le matla a khomphutha ho koetlisa ka katleho. 