01. Intro

Naive Bayes is a supervised machine learning algorithm that can be trained to classify data into multi-class categories. In the heart of Naive Bayes algorithm is the probabilistic model that computes the conditional probabilities of the input features and assigns the probability distributions to each of possible classes.

In this lesson, we will review the conditional probability and Bayes Rule. Next, we will learn how Naive Bayes algorithm works. At the end of the lesson, you will do a coding exercise to apply Naive Bayes in one of the Natural Language Processing (NLP) tasks, ie. spam emails classification, using Scikit-Learn library.