Part 4 introduces deep learning and reinforcement learning.

• Chapter 17, Deep Learning, introduces Keras, TensorFlow and PyTorch, the most popular deep learning frameworks and illustrates how to train and tune various architectures.
• Chapter 18, Recurrent Neural Networks, presents RNNs for time series data
  
• Chapter 19, Convolutional Neural Networks, illustrates how to use CNNs with image and text data
• Chapter 20, Autoencoders and Generative Adversarial Nets, shows how to use deep neural networks for unsupervised learning with autoencoders and presents GANs that produce synthetic data
• Chapter 21, Reinforcement Learning, demonstrates the use of reinforcement learning to build dynamic agents that learn a policy function based on rewards using the OpenAI gym platform