Getting Started with TensorFlow: Efficient, scalable, and user-friendly machine learning for all

Zaccone, Giancarlo

ISBN 10: 1786468573 / ISBN 13: 9781786468574

Published by Packt Publishing, 2016

About this Item

Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind. Seller Inventory # wbs3289289685

Bibliographic Details

Title: Getting Started with TensorFlow: Efficient, ...

Publisher: Packt Publishing

Publication Date: 2016

Binding: Soft cover

Condition: Like New

About this title

Synopsis:

Get up and running with the latest numerical computing library by Google and dive deeper into your data!

Key Features

• Get the first book on the market that shows you the key aspects TensorFlow, how it works, and how to use it for the second generation of machine learning
• Want to perform faster and more accurate computations in the field of data science? This book will acquaint you with an all-new refreshing library-TensorFlow!
• Dive into the next generation of numerical computing and get the most out of your data with this quick guide

Book Description

Google's TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural networks.

This book takes you through the practical software implementation of various machine learning techniques with TensorFlow. In the first few chapters, you'll gain familiarity with the framework and perform the mathematical operations required for data analysis. As you progress further, you'll learn to implement various machine learning techniques such as classification, clustering, neural networks, and deep learning through practical examples.

By the end of this book, you'll have gained hands-on experience of using TensorFlow and building classification, image recognition systems, language processing, and information retrieving systems for your application.

What you will learn

• Install and adopt TensorFlow in your Python environment to solve mathematical problems
• Get to know the basic machine and deep learning concepts
• Train and test neural networks to fit your data model
• Make predictions using regression algorithms
• Analyze your data with a clustering procedure
• Develop algorithms for clustering and data classification
• Use GPU computing to analyze big data

About the Author:

Giancarlo Zaccone has more than 10 years of experience managing research projects in both the scientific and industrial domains. He worked as researcher at the C.N.R, the National Research Council, where he was involved in projects related to parallel numerical computing and scientific visualization.

Currently, he is a senior software engineer at a consulting company developing and maintaining software systems for space and defence applications. Giancarlo holds a master's degree in physics from the Federico II of Naples and a 2nd level postgraduate master course in scientific computing from La Sapienza of Rome.

He has already been a Packt author for the following book: Python Parallel Programming Cookbook.

You can contact him at https://it.linkedin.com/in/giancarlozaccone