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Chapter 11: Implementing a Multilayer Artificial Neural Network from Scratch

Chapter Outline

  • Modeling complex functions with artificial neural networks
    • Single-layer neural network recap
    • Introducing the multilayer neural network architecture
    • Activating a neural network via forward propagation
  • Classifying handwritten digits
    • Obtaining the MNIST dataset
    • Implementing a multilayer perceptron
    • Coding the neural network training loop
    • Evaluating the neural network performance
  • Training an artificial neural network
    • Computing the loss function
    • Developing your intuition for backpropagation
    • Training neural networks via backpropagation
  • About the convergence in neural networks
  • A few last words about the neural network implementation
  • Summary

Please refer to the README.md file in ../ch01 for more information about running the code examples.