<prompt> Mehlala e 5 ea marang-rang a maiketsetso a neural ke afe?nan  <response>: Instruction in English: What are 5 examples of artificial neural networks? . Response in English: 1. Convolutional Neural Network CNN: A type of deep neural network often used in image recognition and processing tasks, consisting of multiple layers of connected neurons which apply filters to input data.2. Recurrent Neural Network RNN: A class of neural networks where connections between nodes form a directed graph along a sequence that allows it to use internal memory to process sequences of inputs.3. Feedforward Neural Network FNN: The most basic type of artificial neural network wherein information moves only forward through the different layers of neurons. They can be used for approximation, regression and classification tasks.4. Long Short-Term Memory LSTM: A type of recurrent neural network capable of learning long-term dependencies in data by incorporating memory cells that can maintain information for long periods of time. LSTMs are commonly used in Natural Language Processing.5. Autoencoder: A type of neural network used to learn data representations in an unsupervised manner. Autoencoders are composed of two parts, an encoder and a decoder, and are typically used in data denoising, and dimensionality reduction. . Response in Sesotho: 1. Convolutional Neural Network CNN: Mofuta oa marang-rang a tebileng a methapo ea kutlo e atisang ho sebelisoa mesebetsing ea ho lemoha litšoantšo le ho sebetsa, e nang le likarolo tse ngata tsa li-neuron tse hokahaneng tse sebelisang li-filters ho data ea ho kenya. 2. Recurrent Neural Network RNN: Sehlopha sa marang-rang a marang-rang moo likamano pakeng tsa li-node li theha graph e tobileng hammoho le tatellano e lumellang hore e sebelise mohopolo oa ka hare ho sebetsana le tatellano ea lintho tse kenang. 3. Feedforward Neural Network FNN: Mofuta oa motheo ka ho fetisisa oa marang-rang a maiketsetso ao boitsebiso bo fetelang pele feela ka lihlopha tse fapaneng tsa methapo. Li ka sebelisoa bakeng sa ho lekanyetsa, ho fokotsa le ho hlophisa mesebetsi. 4. Memori ea Nako e Khutšoane ea Nako e Telele LSTM: Mofuta oa marang-rang a tloaelehileng a neural a khonang ho ithuta ho itšetleha ka nako e telele ho data ka ho kenyelletsa lisele tsa mohopolo tse ka bolokang boitsebiso ka nako e telele. Li-LSTM li sebelisoa hangata ho Natural Language Processing. 5. Autoencoder: Mofuta oa marang-rang a neural o sebelisetsoang ho ithuta liemeli tsa data ka mokhoa o sa laoleheng. Li-autoencoder li entsoe ka likarolo tse peli, encoder le decoder, me hangata li sebelisoa ho hlahisa data, le ho fokotsa boholo. 