Mastering TensorFlow 2.x is a must to read and practice if you are interested in building various kinds of neural networks with high level TensorFlow and Keras APIs. The book begins with the basics of TensorFlow and neural network concepts, and goes into specific topics like image classification, object detection, time series forecasting and Generative Adversarial Networks. While we are practicing TensorFlow 2.6 in this book, the version of Tensorflow will change with time; however you can still use this book to witness how Tensorflow outperforms. This book includes the use of a local Jupyter notebook and the use of Google Colab in various use cases including GAN and Image classification tasks. While you explore the performance of TensorFlow, the book also covers various concepts and in-detail explanations around reinforcement learning, model optimization and time series models.TABLE OF CONTENTS1. Getting started with TensorFlow 2.x2. Machine Learning with TensorFlow 2.x3. Keras based APIs4. Convolutional Neural Networks in Tensorflow5. Text Processing with TensorFlow 2.x6. Time Series Forecasting with TensorFlow 2.x7. Distributed Training and DataInput pipelines8. Reinforcement Learning9. Model Optimization10. Generative Adversarial Networks