<prompt> Hlalosa likarolo tse tharo tsa mantlha tsa netweke ea methapo.nan  <response>: Instruction in English: Describe three primary components of a neural network. . Response in English: A neural network is a type of machine learning model designed to work similarly to the human brain. The three primary components of a neural network are neurons, synapses, and layers.1. Neurons: Also known as nodes or units, neurons are the basic units of a neural network. Each neuron receives input from other neurons or external data, processes the input by performing a weighted sum and passing the result through an activation function before sending the output to other neurons or providing the final output.2. Synapses: Synapses are the connections between neurons, which are responsible for transmitting data from one neuron to another. Each connection has an associated weight value, which determines the strength of the connection between neurons. Adjusting the weights of the connections during the training process allows the neural network to learn from the input data.3. Layers: A neural network is typically composed of multiple layers: an input layer, one or more hidden layers, and an output layer. The input layer receives the input data, and the output layer provides the final output of the model. The hidden layers are responsible for processing the input data and extracting features relevant to the prediction task. Each layer is made up of multiple neurons connected by synapses. . Response in Sesotho: Neural network ke mofuta oa mochini oa ho ithuta o etselitsoeng ho sebetsa ka mokhoa o tsoanang le boko ba motho. Likarolo tse tharo tsa mantlha tsa marang-rang a methapo ke li-neurone, li-synapses, le li-layers. 1. Neurons: E tsejoang hape ka hore ke li-node kapa li-unit, li-neuron ke likarolo tsa mantlha tsa netweke ea methapo. Neuron e ngoe le e ngoe e amohela tlhahiso ho tsoa ho li-neuron tse ling kapa data ea kantle, e sebetsana le ho kenya letsoho ka ho etsa chelete e boima le ho fetisa sephetho ka tsebetso ea tsebetso pele e romella tlhahiso ho li-neurone tse ling kapa e fana ka tlhahiso ea ho qetela. 2. Synapses: Li-synapses ke likhokahano lipakeng tsa li-neuron, tse ikarabellang bakeng sa ho fetisetsa data ho tloha ho neuron e ngoe ho ea ho e ngoe. Khokahano e ngoe le e ngoe e na le boleng ba boima bo amanang le bona, bo khethollang matla a khokahano lipakeng tsa methapo ea kutlo. Ho fetola boima ba likhokahano nakong ea thupelo ho lumella marang-rang a neural ho ithuta ho tsoa ho data e kentsoeng. 3. Likarolo: Neural network hangata e entsoe ka mekhahlelo e mengata: lera le kenyang, le le leng kapa tse ngata tse patehileng, le karolo e hlahisoang. Lera la ho kenya le fumana data ea ho kenya, me sekhahla sa tlhahiso se fana ka tlhahiso ea ho qetela ea mohlala. Likarolo tse patiloeng li na le boikarabello ba ho sebetsana le data ea ho kenya le ho ntša likarolo tse amanang le mosebetsi oa ho bolela esale pele. Lera le leng le le leng le entsoe ka li-neurone tse ngata tse hokahantsoeng ke li-synapse. 