<prompt> Ntlhalosetse hore na hobaneng ho ithuta ka mochini ho le betere ho feta mananeo a setso.nan  <response>: Instruction in English: Explain to me why machine learning is better than traditional programming. . Response in English: Machine Learning is an application of artificial intelligence that allows a computer program to improve its performance of a task using data, without being explicitly programmed. Traditional programming, on the other hand, relies on explicit instructions and pre-defined rules written by a programmer.There are a few key reasons why machine learning is considered better or more advantageous than traditional programming in many scenarios:1. Handling Complexity: The first and perhaps the most significant advantage of machine learning is its ability to handle and make sense of complex, non-linear, and high-dimensional data. Traditional rule-based programming can become cumbersome when dealing with complicated and dynamic data. In contrast, machine learning algorithms operate by learning patterns in the data and making decisions based on those patterns, making them better suited to handle complex data.2. Adaptability: Machine learning algorithms can adapt and improve their performance over time as they are exposed to new data. For example, a recommendation engine employed by a music app can learn the listeners preferences and then use this information to recommend songs tailored to their taste. Traditional programming methods do not have a mechanism to learn from data and improve over time, which can limit their responsiveness to changing conditions.3. Automating Data Analysis: Machine learning can help automate data analysis and make predictions that would otherwise require a tremendous amount of human time and effort. For instance, imagine writing code that could predict whether a particular transaction is fraudulent, given the large number of features and complex relationships between those features. Instead, a machine learning algorithm can automatically learn the relevant patterns in the data and make predictions with high accuracy.In summary, machine learning offers significant advantages over traditional programming in handling complexity, adapting to new conditions, and automating data analysis. These characteristics make it a powerful tool for tackling problems that would be difficult or impossible to solve using traditional methods. . Response in Sesotho: Ho Ithuta ka Mechini ke tsebeliso ea bohlale ba maiketsetso bo lumellang lenaneo la komporo ho ntlafatsa tsebetso ea lona ea mosebetsi ka ho sebelisa data, ntle le ho hlophisoa ka mokhoa o hlakileng. Lenaneo la setso, ka lehlakoreng le leng, le itšetlehile ka litaelo tse hlakileng le melao e boletsoeng esale pele e ngotsoeng ke moqapi. Ho na le mabaka a maloa a bohlokoa a hore na ke hobaneng ha ho ithuta ka mochine ho nkoa e le molemo kapa ho molemo ho feta lenaneo la setso maemong a mangata: 1. Ho Sebetsana le Mathata: Monyetla oa pele mme mohlomong oa bohlokoa ka ho fetisisa oa ho ithuta mochine ke bokhoni ba oona ba ho sebetsana le ho etsa moelelo o rarahaneng, o se nang thuso. - data e hlakileng, le ea maemo a holimo. Lenaneo le thehiloeng melaong ea setso le ka ba boima ha le sebetsana le lintlha tse rarahaneng le tse matla. Ka lehlakoreng le leng, li-algorithms tsa ho ithuta ka mochini li sebetsa ka mekhoa ea ho ithuta ho data le ho etsa liqeto ho latela lipaterone tseo, ho li etsa hore li tšoanelehe hamolemo ho sebetsana le data e rarahaneng. 2. Ho ikamahanya le maemo: Li-algorithms tsa ho ithuta ka mochini li ka ikamahanya le maemo le ho ntlafatsa tsebetso ea tsona ha nako e ntse e ea ha li ntse li pepesetsoa data e ncha. Ka mohlala, enjene ea likhothaletso e sebelisoang ke app ea mino e ka ithuta likhetho tsa momameli ebe e sebelisa lintlha tsena ho khothaletsa lipina tse ikamahanyang le tatso ea tsona. Mekhoa e tloaelehileng ea mananeo ha e na mokhoa oa ho ithuta ho data le ho ntlafatsa ha nako e ntse e ea, e ka fokotsang ho arabela ha bona ho fetola maemo. 3. Tlhahlobo ea Boitsebiso ka Boiketsetso: Ho ithuta ka mochine ho ka thusa ho iketsetsa tlhahlobo ea lintlha le ho etsa likhakanyo tse neng li ka hloka nako e ngata ea motho le boiteko. Mohlala, nahana ka ho ngola khoutu e ka bolelang esale pele hore na khoebo e itseng ke ea bomenemene, ho latela palo e kholo ea likarolo le likamano tse rarahaneng lipakeng tsa likarolo tseo. Sebakeng seo, algorithm ea ho ithuta mochini e ka ithuta ka bo eona mekhoa e nepahetseng ho data le ho bolela esale pele ka nepo e phahameng. Ka bokhutšoanyane, ho ithuta ka mochini ho fana ka melemo e mengata ho feta lenaneo la setso ho sebetsana le ho rarahana, ho ikamahanya le maemo a macha, le ho itlhahloba ka boiketsetso ba data. Litšobotsi tsena li etsa hore e be sesebelisoa se matla sa ho sebetsana le mathata ao ho ka bang thata kapa ho ke keng ha khoneha ho a rarolla ho sebelisoa mekhoa ea setso. 