Chapter 5. Machine Learning
Dataism says that the universe consists of data flows, and the value of any phenomenon or entity is determined by its contribution to data processing….Dataism thereby collapses the barrier between animals [humans] and machines, and expects electronic algorithms to eventually decipher and outperform biochemical algorithms.
Yuval Noah Harari (2015)
Machine learning is the scientific method on steroids. It follows the same process of generating, testing, and discarding or refining hypotheses. But while a scientist may spend his or her whole life coming up with and testing a few hundred hypotheses, a machine learning system can do the same in a second. Machine learning automates discovery. It’s no surprise, then, that it’s revolutionizing science as much as it’s revolutionizing business.
Pedro Domingos (2015)
This chapter is about machine learning as a process. Although it uses specific algorithms and specific data for illustration, the notions and approaches discussed in this chapter are general in nature. The goal is to present the most important elements of machine learning in a single place and in an easy-to-understand and easy-to-visualize manner. The approach of this chapter is practical and illustrative in nature, omitting most technical details throughout. In that sense, the chapter provides a kind of blueprint for later, more realistic machine learning applications.
“Learning” briefly discusses the very notion of a machine that learns. “Data” ...