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TensorFlow Machine Learning Cookbook

You're reading from   TensorFlow Machine Learning Cookbook Over 60 recipes to build intelligent machine learning systems with the power of Python

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789131680
Length 422 pages
Edition 2nd Edition
Languages
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Authors (2):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Nick McClure Nick McClure
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Nick McClure
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow FREE CHAPTER 2. The TensorFlow Way 3. Linear Regression 4. Support Vector Machines 5. Nearest-Neighbor Methods 6. Neural Networks 7. Natural Language Processing 8. Convolutional Neural Networks 9. Recurrent Neural Networks 10. Taking TensorFlow to Production 11. More with TensorFlow 12. Other Books You May Enjoy

Introduction

Neural networks are currently breaking records in tasks such as image and speech recognition, reading handwriting, understanding text, image segmentation, dialog systems, autonomous car driving, and so much more. While some of these aforementioned tasks will be covered in later chapters, it is important to introduce neural networks as an easy-to-implement machine learning algorithm, so that we can expand on it later.

The concept of a neural network has been around for decades. However, it only recently gained traction because we now have the computational power to train large networks because of advances in processing power, algorithm efficiency, and data sizes.

A neural network is basically a sequence of operations applied to a matrix of input data. These operations are usually collections of additions and multiplications followed by the application of non-linear...

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