Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By : Nick McClure, Sujit Pal
Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By: Nick McClure, Sujit Pal

Overview of this book

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.
Table of Contents (13 chapters)

Introduction

So far, we have only considered machine learning algorithms that mostly operate on numerical inputs. If we want to use text, we must find a way to convert the text into numbers. There are many ways to do this, and we will explore a few common ways to do so in this chapter.

If we consider the sentence TensorFlow makes machine learning easy, we could convert the words to numbers in the order that we observe them. This would make the sentence become 1 2 3 4 5. Then when we see a new sentence, machine learning is easy, we can translate this as 3 4 0 5, denoting words we haven't seen with an index of zero. With these two examples, we have limited our vocabulary to six numbers. With large pieces of text, we can choose how many words we want to keep, and usually keep the most frequent words, labeling everything else with a zero index.

If the word learning has a numerical...