O'Reilly logo

Principles of Data Science by Sinan Ozdemir

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Chapter 11. Predictions Don't Grow on Trees – or Do They?

In this chapter, we will be looking at three types of machine learning algorithms. The first two being examples of supervised learning while the final algorithm being an example of unsupervised learning.

Our goal in this chapter is to see and apply concepts learned from previous chapters in order to construct and use modern learning algorithms in order to glean insights and make predictions on real data sets. While we explore the following algorithms, we should always remember that we are constantly keeping our metrics in mind.

Let's get to it!

Naïve Bayes classification

Let's get right into it! Let's begin with Naïve Bayes classification. This machine learning model relies heavily on results ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required