Includes index.

Machine learning landscape -- End-to-end machine learning project -- Classification -- Training models -- Support vector machines -- Decision trees -- Ensemble learning and random forests -- Dimensionality reduction -- Unsupervised learning techniques -- Introduction to artificial neural networks with Keras -- Training deep neural networks -- Custom models and training with TensorFlow -- Loading and preprocessing data with TensorFlow -- Deep computer vision using convolutional neural networks -- Processing sequences using RNNs and CNNs -- Natural landscape processing with RNNs and attention -- Representation learning and generative learning using autoencoders and GANs -- Reinforcement learning -- Training and deploying TensorFlow models at scale.