<prompt> Lisebelisoa tse fapaneng tsa ho ithuta ka mochini ke life?nan  <response>: Instruction in English: What are the different uses of machine learning? . Response in English: Machine learning is a subset of artificial intelligence AI that involves the use of algorithms to learn from and make predictions or decisions based on data. Some of its most common applications include:1. Predictive Modelling: Machine learning algorithms are used to analyze historical data and make predictions about future trends, events or behaviors. Common applications include predicting stock prices, customer behavior or the likelihood of a disease outbreak.2. Image and Speech Recognition: Machine learning is extensively used in computer vision and speech recognition technologies. It can identify patterns in visual or audio data to recognize and classify images or speech.3. Recommender Systems: Machine learning algorithms are used to develop recommender systems that provide personalized recommendations to users, such as products or services they may be interested in, based on their past behavior and preferences.4. Fraud Detection: Machine learning algorithms can analyze large amounts of data to detect fraudulent activities, such as credit card fraud or insurance frauds.5. Natural language processing: Machine learning is widely used in natural language processing NLP, which involves interaction between computers and humans using natural language. NLP is used in applications such as language translation, sentiment analysis and text summarization.Overall, the use of machine learning is widespread and can be applied in a variety of industries and fields, including finance, healthcare, marketing, among others. . Response in Sesotho: Ho ithuta ka mochini ke karoloana ea bohlale ba maiketsetso AI e kenyelletsang tsebeliso ea li-algorithms ho ithuta le ho etsa likhakanyo kapa liqeto tse thehiloeng ho data. Tse ling tsa litsebetso tsa eona tse tloaelehileng li kenyelletsa: 1. Predictive Modelling: Mekhoa ea ho ithuta ka mochine e sebelisetsoa ho hlahloba lintlha tsa histori le ho bolela esale pele ka mekhoa, liketsahalo kapa boitšoaro ba nakong e tlang. Lisebelisoa tse tloaelehileng li kenyelletsa ho bolela esale pele litheko tsa thepa, boitšoaro ba bareki kapa monyetla oa ho qhoma ha lefu. 2. Tlhokomeliso ea Litšoantšo le Puo: Ho ithuta ka mochine ho sebelisoa haholo ponong ea khomphieutha le theknoloji ea ho lemoha puo. E ka khetholla lipaterone ho data ea pono kapa ea molumo ho lemoha le ho arola litšoantšo kapa puo. 3. Recommender Systems: Mekhoa ea ho ithuta ka mochine e sebelisetsoa ho hlahisa mekhoa e khothaletsoang e fanang ka litlhahiso tsa motho ka mong ho basebelisi, tse kang lihlahisoa kapa litšebeletso tseo ba ka li thahasellang, ho latela boitšoaro ba bona ba nakong e fetileng le lintho tseo ba li ratang. 4. Ho Fumana Bomenemene: Mekhoa ea ho ithuta ka mochine e ka hlahloba lintlha tse ngata ho bona liketso tsa bolotsana, tse kang bomenemene ba karete ea mokitlane kapa bomenemene ba inshorense. 5. Tsebetso ea puo ea tlhaho: Ho ithuta ka mochine ho sebelisoa haholo ho sebetsa puo ea tlhaho NLP, e kenyelletsang tšebelisano pakeng tsa likhomphieutha le batho ba sebelisang puo ea tlhaho. NLP e sebelisoa litsebetsong tse joalo ka phetolelo ea puo, tlhahlobo ea maikutlo le kakaretso ea mongolo. Ka kakaretso, tsebeliso ea ho ithuta ka mochini e atile mme e ka sebelisoa liindastering le masimong a fapaneng, ho kenyeletsoa lichelete, tlhokomelo ea bophelo bo botle, mebaraka, hara tse ling. 