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2023.09.07 10:15 [2744650] data 3N9tKixzqTYWnEXQxrDQ5pBTGvQd6sFsvmV > SELF 0.00000000 Waves
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In a neural network, information is passed through multiple layers of neurons. Each neuron receives inputs, applies an activation function to those inputs, and then passes the output to the next layer. This process continues until the final layer produces the desired output.
Neural networks learn by adjusting the strength of connections between neurons, known as weights, based on the input data. This training process helps the network improve its accuracy and make predictions on new, unseen data.
There are different types of neural networks, including feedforward neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and others. Each type is suited for different types of data and tasks." -> null
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