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The document discusses various types of neural networks, including Feedforward Neural Networks (FNN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), highlighting their unique architectures and applications. It also covers different activation functions such as Sigmoid, Tanh, ReLU, Leaky ReLU, and Softmax, explaining their characteristics and use cases in deep learning. Each type of network and activation function has its advantages and limitations, particularly in handling differe

Author

asitghoshasitghosh71

Language

EN