Book description
Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects
Key Features
 Use machine learning and deep learning principles to build realworld projects
 Get to grips with TensorFlow's impressive range of module offerings
 Implement projects on GANs, reinforcement learning, and capsule network
Book Description
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits  simplicity, efficiency, and flexibility  of using TensorFlow in various realworld projects. With the help of this book, you'll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem.
To start with, you'll get to grips with using TensorFlow for machine learning projects; you'll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification.
As you make your way through the book, you'll build projects in various realworld domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You'll learn how to use the TensorFlow on Spark API and GPUaccelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts.
By the end of this book, you'll have gained the required expertise to build fullfledged machine learning projects at work.
What you will learn
 Understand the TensorFlow ecosystem using various datasets and techniques
 Create recommendation systems for quality product recommendations
 Build projects using CNNs, NLP, and Bayesian neural networks
 Play PacMan using deep reinforcement learning
 Deploy scalable TensorFlowbased machine learning systems
 Generate your own book script using RNNs
Who this book is for
TensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. This book is also for you if you want to build endtoend projects in the machine learning domain using supervised, unsupervised, and reinforcement learning techniques
Publisher resources
Table of contents
 Title Page
 Copyright and Credits
 Dedication
 About Packt
 Contributors
 Preface
 1: Overview of TensorFlow and Machine Learning
 2: Using Machine Learning to Detect Exoplanets in Outer Space
 3: Sentiment Analysis in Your Browser Using TensorFlow.js
 4: Digit Classification Using TensorFlow Lite
 5: Speech to Text and Topic Extraction Using NLP
 6: Predicting Stock Prices using Gaussian Process Regression
 7: Credit Card Fraud Detection using Autoencoders
 8: Generating Uncertainty in Traffic Signs Classifier Using Bayesian Neural Networks
 9: Generating Matching Shoe Bags from Shoe Images Using DiscoGANs
 10: Classifying Clothing Images using Capsule Networks

11: Making Quality Product Recommendations Using TensorFlow
 Recommendation systems
 Contentbased filtering
 Collaborative filtering
 Hybrid systems
 Matrix factorization
 Introducing the Retailrocket dataset
 Exploring the Retailrocket dataset
 Preprocessing the data
 The matrix factorization model for Retailrocket recommendations
 The neural network model for Retailrocket recommendations
 Summary
 Questions
 Further reading
 12: Object Detection at a Large Scale with TensorFlow
 13: Generating Book Scripts Using LSTMs
 14: Playing Pacman Using Deep Reinforcement Learning
 15: What is Next?
 Other Books You May Enjoy
Product information
 Title: TensorFlow Machine Learning Projects
 Author(s):
 Release date: November 2018
 Publisher(s): Packt Publishing
 ISBN: 9781789132212
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