Chapter 1. What is machine learning?
This chapter covers
- Machine-learning basics
- Advantages of machine learning over traditional approaches
- Overview of the basic machine-learning workflow
- Overview of advanced methods for improving model performance
In 1959, an IBM computer scientist named Arthur Samuel wrote a computer program to play checkers. Each board position was assigned a score based on its likelihood of leading to a win. At first, scores were based on a formula using factors such as the number of pieces on each side and the number of kings. It worked, but Samuel had an idea about how to improve its performance. He had the program play thousands of games against itself and used the results to refine the positional scoring. By the mid-1970s, the program had achieved the proficiency of a respectable amateur player.[1]
1Jonathan Schaeffer, One Jump Ahead: Computer Perfection at Checkers (New York: Springer, 2009).
Samuel had written a computer program that was able to improve its own performance through experience. It learned—and machine learning (ML) was born.