Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with
complete examples. The book begins with introducing TensorFlow 2.0 framework and the major
changes from its last release. Next it focuses on building Supervised Machine Learning models
using TensorFlow 2.0. It also demonstrates how to build models using customer estimators.
Further it explains how to use TensorFlow 2.0 API to build machine learning and deep learning
models for image classification using the standard as well as custom parameters. You'll review
sequence predictions saving serving deploying and standardized datasets and then deploy
these models to production. All the code presented in the book will be available in the form of
executable scripts at Github which allows you to try out the examples and extend them in
interesting ways. What You'll Learn Review the new features of TensorFlow 2.0 Use TensorFlow
2.0 to build machine learning and deep learning models Perform sequence predictions using
TensorFlow 2.0 Deploy TensorFlow 2.0 models with practical examples Who This Book Is For Data
scientists machine and deep learning engineers.
