IN THIS CHAPTER
Using linear and logistic regression
Understanding Bayes theorem and using it for naïve classification
Predicting on the basis of cases being similar with kNN
“The goal is to turn data into information, and information into insight.”
— CARLY FIORINA
In this chapter, you start to explore all the algorithms and tools necessary for learning from data (the training phase) and being capable of predicting a numeric estimate (for example, house pricing) or a class (for instance, the species of an Iris flower) given a new example that you didn’t have before. In this chapter, you start with the simplest algorithms and work toward more complex ones.