Chapter 1. Machine learning basics

 

This chapter covers

  • A brief overview of machine learning
  • Key tasks in machine learning
  • Why you need to learn about machine learning
  • Why Python is so great for machine learning

I was eating dinner with a couple when they asked what I was working on recently. I replied, “Machine learning.” The wife turned to the husband and said, “Honey, what’s machine learning?” The husband replied, “Cyberdyne Systems T-800.” If you aren’t familiar with the Terminator movies, the T-800 is artificial intelligence gone very wrong. My friend was a little bit off. We’re not going to attempt to have conversations with computer programs in this book, nor are we going to ask a computer the meaning of life. With machine learning we can gain insight from a dataset; we’re going to ask the computer to make some sense from data. This is what we mean by learning, not cyborg rote memorization, and not the creation of sentient beings.

1.1. What is machine learning?

1.2. Key terminology

1.3. Key tasks of machine learning

1.4. How to choose the right algorithm

1.5. Steps in developing a machine learning application

1.6. Why Python?

1.7. Getting started with the NumPy library

1.8. Summary