<prompt> Hlalosa hore na neuron ea maiketsetso e sebetsa joang.nan  <response>: Instruction in English: Explain how an artificial neuron works. . Response in English: An artificial neuron, also known as a perceptron, is a mathematical model that seeks to emulate the function of a biological neuron found in the brain. It is one of the fundamental building blocks of artificial neural networks, which are used in machine learning to recognize patterns in data and make predictions.At a basic level, an artificial neuron receives input signals from other neurons or from external sources through its input channels, which are called dendrites. Each input signal is assigned a weight that represents the strength of connection between the two neurons. The inputs are then summed up within the neuron, typically using a weighted sum formula. This sum is then presented as input to an activation function, which transforms the sum into an output signal.The output signal is transmitted through the neurons output channel, known as the axon. The neurons activation function, which could be a sigmoid, a linear, a step, or some other non-linear function, shapes the output signal so that it ranges from 0 to 1 or from -1 to 1. The output signal is then used as an input to other neurons or is part of the output of the neural network.Through a process called training, the weights of the artificial neuron are adjusted based on the desired output. This training process involves a learning algorithm, such as backpropagation, which compares the actual output of the neural network to a desired output and calculates the error. The error is then propagated back through the neural network, and the weights of the neural connections are adjusted to minimize the error. With repeated training, the artificial neuron is able to correctly classify and recognize patterns in the data. . Response in Sesotho: Neuron ea maiketsetso, e tsejoang hape e le perceptron, ke mohlala oa lipalo o batlang ho etsisa tšebetso ea neuron ea baeloji e fumanoang bokong. Ke e ngoe ea likarolo tsa mantlha tsa marang-rang a maiketsetso a neural, a sebelisoang thutong ea mochini ho lemoha mekhoa ea data le ho bolela esale pele. Boemong ba mantlha, neuron ea maiketsetso e fumana matšoao a kenyellelitsoeng ho tsoa ho li-neuron tse ling kapa mehloling e kantle ka mecha ea eona ea ho kenya, e bitsoang li-dendrites. Letšoao le leng le le leng la ho kenya le abeloa boima bo emelang matla a khokahano lipakeng tsa li-neuron tse peli. Lintho tse kenang li akaretsoa ka hara neuron, hangata ho sebelisoa foromo e lekantsoeng ea kakaretso. Kakaretso ena e hlahisoa e le kenyelletso ea tsebetso ea tsebetso, e fetolang kakaretso hore e be letsoao la tlhahiso. Letšoao la tlhahiso le fetisoa ka mocha oa tlhahiso ea neuron, o tsejoang e le axon. Tsebetso ea tšebetso ea neuron, e ka bang sigmoid, mola, mohato, kapa tsebetso e ngoe e se nang moeli, e bopa letsoao la tlhahiso hore le tlohe ho tloha ho 0 ho isa ho 1 kapa ho tloha ho -1 ho isa ho 1. Joale ho sebelisoa letšoao la tlhahiso. e le ho kenya letsoho ho li-neurone tse ling kapa ke karolo ea tlhahiso ea marang-rang a methapo. Ka mokhoa o bitsoang koetliso, boima ba neuron ea maiketsetso bo lokisoa ho latela tlhahiso e lakatsehang. Tsebetso ena ea koetliso e kenyelletsa algorithm ea ho ithuta, joalo ka ho khutlisetsa morao, e bapisang tlhahiso ea nete ea marang-rang a neural le sephetho se lakatsehang ebe e bala phoso. Phoso e fetisetsoa morao ka marang-rang a neural, me litekanyo tsa likhokahano tsa neural lia lokisoa ho fokotsa phoso. Ka koetliso e pheta-phetoang, neuron ea maiketsetso e khona ho hlophisa ka nepo le ho lemoha mekhoa ea data. 