<prompt> Hlalosa liphapang tse tharo pakeng tsa neural network le sefate sa liqetonan  <response>: Instruction in English: Describe three differences between a neural network and a decision tree . Response in English: 1. Structure: A neural network is composed of interconnected neurons arranged in layers, where the input data is processed through these layers to produce the output, whereas a decision tree is a tree-like structure where each node represents a decision or test, and the branches represent the possible outcomes of the decision.2. Learning algorithm: Neural networks use backpropagation to learn and adjust the weights of the connections between neurons based on the error between the predicted and actual output, whereas decision trees use recursive partitioning algorithms to build the tree, selecting the best attribute to split the data at each step based on a criterion such as information gain or Gini index.3. Handling of continuous and categorical data: Neural networks are generally better suited for handling continuous data, although they can also handle categorical data with appropriate encoding, whereas decision trees can handle both continuous and categorical data, with different splitting criteria for each. . Response in Sesotho: 1. Sebopeho: Marang-rang a marang-rang a entsoe ka li-neurone tse hokahaneng tse hlophisitsoeng ka mekhahlelo, moo data ea ho kenya e sebetsoa ka lihlopha tsena ho hlahisa tlhahiso, athe sefate sa liqeto ke sebopeho se kang sefate moo node e ngoe le e ngoe e emelang qeto kapa teko, le makala a emela liphello tse ka bang teng tsa qeto. 2. Algorithm ea ho ithuta: Marang-rang a Neural a sebelisa li-backpropagation ho ithuta le ho lokisa boima ba likhokahano lipakeng tsa li-neurone tse ipapisitseng le phoso lipakeng tsa sephetho se boletsoeng esale pele le sa nete, athe lifate tsa liqeto li sebelisa li-algorithms tsa ho arola li-recursive ho aha sefate, ho khetha tšobotsi e ntle ka ho fetisisa ea ho arola sefate. data mohatong o mong le o mong o ipapisitse le maemo a kang ho fumana tlhahisoleseling kapa index ea Gini. 3. Ho sebetsana le lintlha tse tsoelang pele le tsa lihlopha: Marang-rang a Neural ka kakaretso a loketse hamolemo bakeng sa ho sebetsana le data e tsoelang pele, le hoja a ka boela a sebetsana le lintlha tsa lihlopha tse nang le encoding e nepahetseng, athe lifate tsa liqeto li khona ho sebetsana le lintlha tse tsoelang pele le tsa lihlopha, tse nang le mekhoa e fapaneng ea ho arola e ngoe le e ngoe. 