Video Tutorial: Naive Bayes Classifiers

Naive Bayes classifiers are simple but powerful tools for classification in statistics and machine learning.  In this video tutorial, I use a simulated data set and illustrate the mathematical details of how this technique works.

In my recent episode on The Central Equilibrium about word embeddings and text classification, Mandy Gu used naive Bayes classifiers to determine if a sentence is toxic or non-toxic – a very common objective when moderating discussions in online forums.  If you are not familiar with naive Bayes classifiers, then I encourage you to watch this video first before watching Mandy’s episode on The Central Equilibrium.

Mandy Gu on Word Embeddings and Text Classification – The Central Equilibrium – Episode 9

I am so grateful to Mandy Gu for being a guest on The Central Equilibrium to talk about word embeddings and text classification.  She began by showing how data from text can be encoded in vectors and matrices, and then she used a naive Bayes classifier to classify sentences as toxic or non-toxic – a very common problem for moderating discussions in online forums.  I learned a lot from her in this episode, and you can learn more from Mandy on her Medium blog.

If you are not familiar with naive Bayes classifiers, then I encourage you to watch my video tutorial about this topic first.