TensorFlow Deep Learning Projects - 10 real-world projects on computer vision, machine transition, chatbots, and reinforcement learning

Luca Massaron

Alberto Boschetti

Alexey Grigorev

Abhishek Thakur

Rajalingappaa Shanmugamani

Technologie

Publié par Packt Publishing, le 30 mars 2018

307 pages

Résumé

TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models with very high accuracy. This book is your guide to mastering deep learning with TensorFlow with the help of10 real-world projects. TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.