Machine Learning for Beginners, Part 7 – Naïve Bayes

In my last blog, I discussed k-Nearest Neighbor machine learning algorithms with an example that was hopefully easy to understand for beginners. During the summer of 2017 I began a five-part series on types of machine learning. That series included more details about K-means clustering, Singular Value Decomposition, Principal Component Analysis, Apriori and Frequent Pattern-Growth. Today I want to expand on the ideas presented in my Naive Bayes "Data Science in 90 Seconds" You Tube video and continue the discussion in plain language. If you recall from earlier discussions, unsupervised machine learning is the'task of inferring a function to describe hidden structure from unlabeled data'.