9 lines
716 B
TeX
9 lines
716 B
TeX
Modeling complex functions with artificial neural networks
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Single-layer neural network recap
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Introducing the multi-layer neural network architecture
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Activating a neural network via forward propagation
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Classifying handwritten digits
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Obtaining the MNIST dataset
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Implementing a multi-layer perceptron
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Training an artificial neural network
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Computing the logistic cost function
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Training neural networks via backpropagation
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Developing your intuition for backpropagation
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Debugging neural networks with gradient checking
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Convergence in neural networks
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Other neural network architectures
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Convolutional Neural Networks
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Recurrent Neural Networks
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A few last words about neural network implementation
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Summary
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