Applied Machine Learning and AI for Engineers

Chapter 1. Machine Learning

Machine learning expands the boundaries of what’s possible by allowing computers to solve problems that were intractable just a few short years ago. From fraud detection and medical diagnoses to product recommendations and cars that “see” what’s in front of them, machine learning impacts our lives every day. As you read this, scientists are using machine learning to unlock the secrets of the human genome. When we one day cure cancer, we will thank machine learning for making it possible.

Machine learning is revolutionary because it provides an alternative to algorithmic problem-solving. Given a recipe, or algorithm, it’s not difficult to write an app that hashes a password or computes a monthly mortgage payment. You code up the algorithm, feed it input, and receive output in return. It’s another proposition altogether to write code that determines whether a photo contains a cat or a dog. You can try to do it algorithmically, but the minute you get it working, you’ll come across a cat or dog picture that breaks the algorithm.

Machine learning takes a different approach to turning input into output. Rather than relying on you to implement an algorithm, it examines a dataset of inputs and outputs and learns how to generate output of its own in a process known as training. Under the hood, special algorithms called learning algorithms fit mathematical models to the data and codify the relationship between data going in and data coming out. Once trained, ...