AI and Machine Learning for Coders

Chapter 1. Introduction to TensorFlow

When it comes to creating artificial intelligence (AI), machine learning (ML) and deep learning are a great place to begin. When getting started, however, it’s easy to get overwhelmed by the options and all the new terminology. This book aims to demystify things for programmers, taking you through writing code to implement concepts of machine learning and deep learning; and building models that behave more as a human does, with scenarios like computer vision, natural language processing (NLP), and more. Thus, they become a form of synthesized, or artificial, intelligence.

But when we refer to machine learning, what in fact is this phenomenon? Let’s take a quick look at that, and consider it from a programmer’s perspective before we go any further. After that, this chapter will show you how to install the tools of the trade, from TensorFlow itself to environments where you can code and debug your TensorFlow models.

What Is Machine Learning?

Before we get into the ins and outs of ML, let’s consider how it evolved from traditional programming. We’ll start by examining what traditional programming is, then consider cases where it is limited. Then we’ll see how ML evolved to handle those cases, and as a result has opened up new opportunities to implement new scenarios, unlocking many of the concepts of artificial intelligence.

Traditional programming involves us writing rules, expressed in a programming language, that act on data and give us answers. ...