# Naïve Bayes Classifiers

# Chapter 1: Introduction

In the introduction, we’ll discuss what Bayes Theorem is, and how it can be used for classification.

# Chapter 2: Naïve Bayes Classification

Machine Learning is very useful but not for every task. With this chapter, you’ll gain a better understanding of what task might require machine learning.

# Chapter 3: Gaussian Naïve Bayes

In this chapter, we’ll show how Naïve Bayes can be used assuming a normal distribution.

# Chapter 4: Bernoulli Naïve Bayes

In this chapter, we’ll show how Naïve Bayes can be used assuming a Bernoulli distribution.

# Chapter 5: Multinomial Naïve Bayes

In this chapter, we’ll show how Naïve Bayes can be used assuming a multinomial distribution.

# Chapter 6: Summary

In this chapter, we’ll summarize what was taught in the previous chapters and provide links to useful resources.