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