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.