Book Image

TensorFlow Machine Learning Cookbook. - Second Edition

By : Sujit Pal, Nick McClure
Book Image

TensorFlow Machine Learning Cookbook. - Second Edition

By: Sujit Pal, Nick McClure

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)

Implementing TF-IDF

Since we can choose the embedding for each word, we might decide to change the weighting on certain words. One such strategy is to up weight useful words and downweight overly common or rare words. The embedding we will explore in this recipe is an attempt to achieve this.

Getting ready

TF-IDF is an acronym that stands for Text Frequency - Inverse Document Frequency. This term is essentially the product of text frequency and inverse document frequency for each word.

In the preceding recipe, we introduced the bag-of-words methodology, which assigned a value of 1 for every occurrence of a word in a sentence. This is probably not ideal as each category of sentence (spam and ham in the preceding recipe&apos...