<prompt> Hlalosa phapang lipakeng tsa thuto e hlokometsoeng le e sa behoang leihlo.nan  <response>: Instruction in English: Describe the difference between supervised and unsupervised learning. . Response in English: Supervised and unsupervised learning are two main types of machine learning methods that are used to train machine learning models. In supervised learning, the machine learning algorithm is trained on a labeled dataset, where the outcome variable or label is known. The goal of the algorithm is to learn the mapping function between the input features and the outcome variable. The algorithm uses this mapping function to make predictions on new, unseen data. Supervised learning algorithms are used for classification and regression tasks, where the outcome variable is categorical or continuous, respectively.In contrast, unsupervised learning does not use labeled data. Instead, the algorithm tries to identify patterns or relationships in the data by finding clusters or groups within the data. The goal of unsupervised learning is to identify underlying structures or features in the data that can be used to describe the data or identify relationships between the data points. Common unsupervised learning algorithms are used for clustering and dimensionality reduction tasks.In summary, the main difference between supervised and unsupervised learning is that supervised learning uses labeled data to learn the mapping function between the input features and the outcome variable, while unsupervised learning tries to identify patterns or relationships in the data by finding clusters or groups within the data without the use of labeled data. . Response in Sesotho: Thuto e hlokometsoeng le e sa laoleheng ke mefuta e meli ea mantlha ea mekhoa ea ho ithuta ka mochini e sebelisoang ho koetlisa mefuta ea ho ithuta ka mochini. Thutong e hlokometsoeng, algorithm ea ho ithuta ka mochini e koetlisetsoa setsing sa data se ngolisitsoeng, moo sephetho se fapaneng kapa leibole se tsejoang. Sepheo sa algorithm ke ho ithuta mosebetsi oa mapa pakeng tsa likarolo tsa ho kenya letsoho le phetoho ea sephetho. Algorithm e sebelisa mosebetsi ona oa mapa ho etsa likhakanyo ho data e ncha, e sa bonahaleng. Li-algorithms tsa ho ithuta tse hlokometsoeng li sebelisoa bakeng sa mesebetsi ea ho arola le ho khutlela morao, moo phetoho ea sephetho e leng ea lihlopha kapa e tsoelang pele, ka ho latellana. Ka lehlakoreng le leng, thuto e sa laoleheng ha e sebelise lintlha tse ngotsoeng. Sebakeng seo, algorithm e leka ho tsebahatsa lipaterone kapa likamano ho data ka ho fumana lihlopha kapa lihlopha ka hara data. Sepheo sa thuto e sa laoleheng ke ho tsebahatsa meaho kapa likarolo tse teng ho data tse ka sebelisoang ho hlalosa lintlha kapa ho tseba likamano lipakeng tsa lintlha tsa data. Mekhoa e tloaelehileng ea ho ithuta e sa hlokomeloe e sebelisoa bakeng sa ho kopanya le ho fokotsa likarolo. Ka bokhutsoanyane, phapang e kholo lipakeng tsa thuto e hlokometsoeng le e sa laoleheng ke hore thuto e hlokometsoeng e sebelisa lintlha tse ngotsoeng ho ithuta mosebetsi oa mapa lipakeng tsa likarolo tse kentsoeng le phapang ea sephetho, athe thuto e sa laoleheng e leka ho khetholla lipaterone kapa likamano ho data ka ho fumana lihlopha kapa lihlopha ka hara. data ntle le tšebeliso ea data e ngolisitsoeng. 