Hands-on deep learning for images with TensorFlow : build intelligent computer vision applications using TensorFlow and Keras / Will Ballard.

Format:

Book

Author/Creator:

Ballard, Will, author.

Language:

English

Subjects (All):

Artificial intelligence.

Physical Description:

1 online resource (92 pages) : illustrations

Edition:

1st edition

Place of Publication:

Birmingham ; Mumbai : Packt, 2018.

System Details:

text file

Biography/History:

Ballard Will: 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, NPR, The Washington Post, and Whole Foods. He has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works (now Bank of America). https: //www. linkedin. com/in/will-ballard-b09115/

Summary:

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.

Contents:

Cover

Title Page

Copyright and Credits

Packt Upsell

Contributors

Table of Contents

Preface

Chapter 1: Machine Learning Toolkit

Installing Docker

The machine learning Docker file

Sharing data

Machine learning REST service

Summary

Chapter 2: Image Data

MNIST digits

Tensors - multidimensional arrays

Turning images into tensors

Turning categories into tensors

Chapter 3: Classical Neural Network

Comparison between classical dense neural networks

Activation and nonlinearity

Softmax

Training and testing data

Dropout and Flatten

Solvers

Hyperparameters

Grid searches

Chapter 4: A Convolutional Neural Network

Convolutions

Pooling

Building a convolutional neural network

Deep neural network

Chapter 5: An Image Classification Server

REST API definition

Trained models in Docker containers

Making predictions

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Index.

Notes:

Includes index.

Description based on print version record.

ISBN:

9781789532517

1789532515

OCLC:

1048788262