Book Image

Machine Learning Using TensorFlow Cookbook

By : Luca Massaron, Alexia Audevart, Konrad Banachewicz
Book Image

Machine Learning Using TensorFlow Cookbook

By: Luca Massaron, Alexia Audevart, Konrad Banachewicz

Overview of this book

The independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data. Dive into recipes on training models, model evaluation, sentiment analysis, regression analysis, artificial neural networks, and deep learning - each using Google’s machine learning library, TensorFlow. This cookbook covers the fundamentals of the TensorFlow library, including variables, matrices, and various data sources. You’ll discover real-world implementations of Keras and TensorFlow and learn how to use estimators to train linear models and boosted trees, both for classification and regression. Explore the practical applications of a variety of deep learning architectures, such as recurrent neural networks and Transformers, and see how they can be used to solve computer vision and natural language processing (NLP) problems. With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement machine learning algorithms in real-world scenarios.
Table of Contents (15 chapters)
Boosted Trees
Reinforcement Learning with TensorFlow and TF-Agents
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Getting Started with TensorFlow 2.x

Google's TensorFlow engine has a unique way of solving problems, allowing us to solve machine learning problems very efficiently. Nowadays, machine learning is used in almost all areas of life and work, with famous applications in computer vision, speech recognition, language translations, healthcare, and many more. We will cover the basic steps to understand how TensorFlow operates and eventually build up to production code techniques later in the pages of this book. For the moment, the fundamentals presented in this chapter are paramount in order to provide you with a core understanding for the recipes found in the rest of this book.

In this chapter, we'll start by covering some basic recipes and helping you to understand how TensorFlow 2.x works. You'll also learn how to access the data used to run the examples in this book, and how to get additional resources. By the end of this chapter, you should have knowledge of the following...