The first group of machine learning techniques that we will explore is generally referred to as regression. Regression is a process through which we can understand how one variable (for example, sales) changes with respect to another variable (for example, number of users). These techniques are useful on their own. However, they are also a good starting point to discuss machine learning techniques because they form the basis of other, more complicated, techniques that we will discuss later in the book.
Generally, regression techniques in machine learning are concerned with predicting continuous values (for example, stock price, temperature, or disease progression). Classification, which we will cover in the next chapter, is concerned with predicting discrete variables, or one of a discrete set of categories (for example, fraud/not fraud, sitting/standing/running, or...
