• 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.