Learning TensorFlow: A Guide to Building Deep Learning Systems

Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics.

Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. You’ll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you’ll know how to build and deploy production-ready deep learning systems in TensorFlow.

• Get up and running with TensorFlow, rapidly and painlessly
• Learn how to use TensorFlow to build deep learning models from the ground up
• Train popular deep learning models for computer vision and NLP
• Use extensive abstraction libraries to make development easier and faster
• Learn how to scale TensorFlow, and use clusters to distribute model training
• Deploy TensorFlow in a production setting

• TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
• Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• Deep Learning with Python
• Deep Learning: A Practitioner's Approach
• Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
• Deep Learning (Adaptive Computation and Machine Learning series)
• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• The Hundred-Page Machine Learning Book
• Introduction to Machine Learning with Python: A Guide for Data Scientists
• Python Data Science Handbook: Essential Tools for Working with Data