Hands-On Deep Learning for Images with TensorFlow - ebook

Explore TensorFlow's capabilities to perform efficient deep learning on images

Key Features

• Discover image processing for machine vision
• Build an effective image classification system using the power of CNNs
• Leverage TensorFlow’s capabilities to perform efficient deep learning

Book Description

TensorFlow is Google’s popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks.

Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow’s capabilities to perform efficient image processing using the power of deep learning. With the help of this book, you will get to grips with the different paradigms of performing deep learning such as deep neural nets and convolutional neural networks, followed by understanding how they can be implemented using TensorFlow.

By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow and Keras.

What you will learn

• Build machine learning models particularly focused on the MNIST digits
• Work with Docker and Keras to build an image classifier
• Understand natural language models to process text and images
• Prepare your dataset for machine learning
• Create classical, convolutional, and deep neural networks
• Create a RESTful image classification server

Who this book is for

Hands-On Deep Learning for Images with TensorFlow is for you if you are an application developer, data scientist, or machine learning practitioner looking to integrate machine learning into application software and master deep learning by implementing practical projects in TensorFlow. Knowledge of Python programming and basics of deep learning are required to get the best out of this book.

Will Ballard is the chief technology officer at GLG, responsible for engineering and IT. He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL.com, NPR, The Washington Post, and Whole Foods. He has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works.com (now Bank of America).