<prompt> Bapisa le ho bapisa Morafo oa Lintlha le Thuto ea Mechini.nan  <response>: Instruction in English: Compare and contrast Data Mining and Machine Learning. . Response in English: Data mining and machine learning are two areas of computer science that are intertwined with each other. While they share some similarities, they also have some differences.Data mining is the process of extracting useful information from large datasets. It involves the use of various techniques such as clustering, classification, and association rule mining to uncover hidden patterns and relationships in data. The goal of data mining is to make sense of and transform raw data into actionable knowledge.On the other hand, Machine learning is a subset of artificial intelligence that involves the development of algorithms that can learn from data and make predictions or decisions based on that data. The goal of machine learning is to create models that can generalize and make accurate predictions or decisions on new, unseen data.One key difference between the two is that data mining is the process of finding correlations or patterns among numerous fields in large relational databases while machine learning uses these patterns and correlations to learn from data and make accurate predictions.In essence, data mining is more exploratory in nature, focused on finding previously unknown patterns or relationships in data. On the other hand, machine learning is more predictive, focused on using known patterns to make predictions or decisions. Additionally, machine learning models can improve over time, as they are exposed to new data, while data mining techniques do not change.Overall, data mining and machine learning are two important tools for extracting knowledge from data. While they share some similarities, they also have some distinct differences, and both have their unique strengths and use cases. . Response in Sesotho: Meepo ea data le ho ithuta ka mochini ke likarolo tse peli tsa mahlale a khomphutha tse hokahaneng. Le hoja ba arolelana lintho tse ling tse tšoanang, ba boetse ba na le phapang e itseng. Merafo ea data ke mokhoa oa ho ntša lintlha tse molemo ho li-dataset tse kholo. E kenyelletsa tsebeliso ea mekhoa e fapaneng e kang ho kopanya, ho arola, le ho tsamaisa melao ea mekhatlo ho senola mekhoa e patiloeng le likamano ho data. Sepheo sa merafo ea data ke ho utloisisa le ho fetola data e tala hore e be tsebo e sebetsang. Ka lehlakoreng le leng, ho ithuta ka Mochini ke karoloana ea bohlale ba maiketsetso bo kenyelletsang ntsetsopele ea li-algorithms tse ka ithutang ho data le ho etsa likhakanyo kapa liqeto tse thehiloeng ho data eo. Sepheo sa ho ithuta ka mochini ke ho theha mefuta e ka akaretsang le ho etsa likhakanyo tse nepahetseng kapa liqeto ho data e ncha, e sa bonahaleng. Phapang e ngoe ea bohlokoa pakeng tsa tse peli ke hore merafo ea data ke mokhoa oa ho fumana likamano kapa mekhoa hara masimo a mangata a marang-rang a maholo a kamano ha thuto ea mochine e sebelisa mekhoa ena le likamano ho ithuta ho tsoa ho data le ho bolela esale pele ka nepo. Ha e le hantle, merafo ea data e ntse e hlahloba haholoanyane ka tlhaho, e shebane le ho fumana mekhoa e neng e sa tsejoe pele kapa likamano ho data. Ka lehlakoreng le leng, ho ithuta ka mochini ho bolela esale pele, ho tsepamisitsoe ho sebelisa mekhoa e tsebahalang ho etsa likhakanyo kapa liqeto. Ho feta moo, mefuta ea ho ithuta ka mochini e ka ntlafala ha nako e ntse e feta, kaha e pepesehetse data e ncha, athe mekhoa ea merafo ea data ha e fetohe. Ka kakaretso, merafo ea data le ho ithuta ka mochini ke lisebelisoa tse peli tsa bohlokoa bakeng sa ho ntša tsebo ho data. Ha ba ntse ba arolelana lintho tse tšoanang, ba boetse ba na le liphapang tse fapaneng, me ka bobeli ba na le matla a bona a ikhethang le linyeoe tsa tšebeliso. 