<prompt> Hlalosa hore na ho ithuta ka mochini ho sebetsa joang.nan  <response>: Instruction in English: Describe how basic machine learning works. . Response in English: Basic machine learning is a type of artificial intelligence in which a computer program is able to learn from data and make predictions or decisions without being explicitly programmed to perform the task. The process typically begins with data collection or providing the program with a data set. This data can be in the form of images, text, or numbers, and will serve as a basis for the programs learning.The next step is to split the data into two sets: a training set and a test set. The training set is used to train the machine learning algorithm, while the test set is used to evaluate how well the algorithm performs.Once the algorithm has been trained, it can be used to make predictions on new data. For example, a basic machine learning algorithm could be trained to identify pictures of cats and dogs. The algorithm would analyze each picture and make a prediction about whether it is an image of a cat or a dog. As the algorithm processes more pictures, it learns from its mistakes and becomes better at identifying the animals correctly.Some common types of basic machine learning algorithms include decision trees, k-nearest neighbors, and linear regression. Each of these algorithms has its own strengths and weaknesses and works best for certain types of data.Overall, basic machine learning is a powerful tool that can be used to analyze and make sense of large amounts of data. By using algorithms that can learn from the data, the program can make predictions or decisions that are far more accurate than a human could achieve on their own. . Response in Sesotho: Ho ithuta ka mochini oa mantlha ke mofuta oa bohlale ba maiketsetso boo ho bona lenaneo la khomphutha le khonang ho ithuta ho tsoa ho data le ho etsa likhakanyo kapa liqeto ntle le ho hlophisoa ka mokhoa o hlakileng ho etsa mosebetsi oo. Tsebetso hangata e qala ka pokello ea data kapa ho fana ka lenaneo ka sete ea data. Lintlha tsena li ka ba ka mokhoa oa litšoantšo, mongolo, kapa linomoro, me li tla sebetsa e le motheo oa thuto ea lenaneo. Mohato o latelang ke ho arola lintlha ka lihlopha tse peli: setsi sa koetliso le sete ea teko. Sehlopha sa koetliso se sebelisetsoa ho koetlisa algorithm ea ho ithuta mochine, ha tlhahlobo ea liteko e sebelisetsoa ho lekola hore na algorithm e sebetsa hantle hakae. Hang ha algorithm e se e koetlisitsoe, e ka sebelisoa ho etsa likhakanyo ho data e ncha. Ka mohlala, algorithm ea motheo ea ho ithuta mochine e ka koetlisoa ho khetholla litšoantšo tsa likatse le lintja. Algorithm e ne e tla sekaseka setšoantšo se seng le se seng ebe e bolela esale pele hore na ke setšoantšo sa katse kapa ntja. Ha algorithm e ntse e sebetsa litšoantšo tse ngata, e ithuta liphosong tsa eona mme e ba betere ho khetholla liphoofolo ka nepo. Mefuta e meng e tloaelehileng ea li-algorithms tsa mantlha tsa ho ithuta mochini e kenyelletsa lifate tsa liqeto, baahisani ba haufi le k, le ho fokotseha ha mela. E ngoe le e ngoe ea mekhoa ena e na le matla le mefokolo ea eona me e sebetsa hantle bakeng sa mefuta e itseng ea data. Ka kakaretso, thuto ea mantlha ea mochini ke sesebelisoa se matla se ka sebelisoang ho sekaseka le ho utloisisa lintlha tse ngata. Ka ho sebelisa li-algorithms tse ka ithutang ho data, lenaneo le ka etsa likhakanyo kapa liqeto tse nepahetseng ho feta kamoo motho a ka fihlelang ka bobona. 