We'll build a Spam Detector using a machine learning model called a Naive Bayes Classifier! This is our first real dip into probability theory in the series; I'll talk about the types of probability, then we'll use Bayes Theorem to help us build our classifier.

Code for this video: https://github.com/llSourcell/naive_bayes_classifier/

Hammad's Winning Code: https://github.com/hammadshaikhha/Math-of-Machine-Learning-Course-by-Siraj/tree/master/Principal%20Component%20Analysis

Kristian's Runner up Code: https://github.com/kwichmann/PCA_and_autoencoders

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More Learning Resources: http://machinelearningmastery.com/naive-bayes-tutorial-for-machine-learning/ http://blog.datumbox.com/machine-learning-tutorial-the-naive-bayes-text-classifier/ http://machinelearningmastery.com/naive-bayes-classifier-scratch-python/ https://www.analyticsvidhya.com/blog/2015/09/naive-bayes-explained/ https://www.youtube.com/watch?v=psHrcSacU9Y https://hackernoon.com/how-to-build-a-simple-spam-detecting-machine-learning-classifier-4471fe6b816e https://www.autonlab.org/tutorials/naive.html

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