The book starts off with a look at what machine learning is and what sorts of things it can be used for. The actual subject of the book gets started at Chapter 3 where we meet linear regression. I'm not at all sure I class regression as ML - it is more classical statistics. What is interesting about this presentation is that the regression problem is solved using gradient descent, i.e an iterative algorithm like many others in machine learning. This is a good idea in that it is a simple way into the idea of iterative learning.

This is Chapter 8 on the book Grokking Machine Learning. Check out the author's YouTube channel Serrano.Academy for lots of machine learning videos! Take 40% off Grokking Machine Learning by entering fccserrano into the discount code box at checkout at manning.com. Naive Bayes is an important machine learning model used for prediction. The naive Bayes model is a purely probabilistic classification model, which means the prediction is a number between 0 and 1, indicating the probability that a label is positive.

Machine learning applications can be found in virtually every aspect of our day-to-day lives. Our product recommendations, social media feeds, email spam filters, traffic predictions, virtual personal assistants, and more, are all driven by machine learning. Companies are increasingly on the hunt for talented machine learning practitioners, so there’s no time like the present to gain those highly sought-after skills!

Written in an approachable manner with great use of very illustrative and applicable examples.