# Naive Bayes Part 1

This is part 1 of naive bayes machine learning tutorial. Naive bayes theorm uses bayes theorm for conditional probability with a naive assumption that the features are not correlated to each other and tries to find conditional probability of target variable given the probabilities of features. We will use titanic survival dataset here and using naive bayes classifier find out the survival probability of titanic travellers. We use sklearn library and python for this beginners machine learning tutorial. GaussianNB is the classifier we use to train our model. There are other classifiers such as MultinomialNB but we will use that in part 2 of the tutorial.

Code: https://github.com/codebasics/py/blob/master/ML/14_naive_bayes/14_naive_bayes_1_titanic_survival_prediction.ipynb Naive bayes theory video: https://www.youtube.com/watch?v=Q8l0Vip5YUw

Topics that are covered in this Video:

00:19 Basics of probability

00:52 Conditional probability

01:52 Bayes theorm

04:37 Coding: titanic crash survival

10:00 GaussianNB classifier