To get the most out of this book

You need to have a basic understanding of neural networks, but this is not mandatory since the topics will be covered from a practical point of view and theoretical information will be provided where needed.

A working knowledge of basic machine learning algorithms and technicalities is a plus. You need a good working knowledge of Python 3. You should already know how to install packages using pip, as well as how to set up your working environment to work with TensorFlow.

The environment setup will be covered in Chapter 1, Getting Started with TensorFlow 2.x.

Download the example code files

The code bundle for the book is hosted on GitHub at https://github.com/PacktPublishing/Machine-Learning-Using-TensorFlow-Cookbook. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://static.packt-cdn.com/downloads/9781800208865_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. For example; "The truncated_normal() function always picks normal values within two standard deviations of the specified mean."

A block of code is set as follows:

import TensorFlow as tf
import NumPy as np 

Any command-line input or output is written as follows:

pip install tensorflow-datasets

Bold: Indicates a new term, an important word, or words that you see on the screen, for example, in menus or dialog boxes, also appear in the text like this. For example: "TF-Agents is a library for reinforcement learning (RL) in TensorFlow."