Summary: If you are like me, who has been trained in statistics and econometrics, not all the terminology used in machine learning is easily understandable. I think that machine learning guys are good marketers and they know how to name their techniques! For example, creating plain vanilla ‘dummy variables’ becomes ‘one hot encoding’ in machine learning :) There are some confusing things too. In statistics bias typically refers to the bias in the estimates. In machine learning it could be the intercept! Anyway, this article provides us with the translation from statistics to machine learning.
Summary: This article provides a listing and a very brief description of 10 machine learning algorithms. For what it is worth, there are actually just 4 machine learning algorithms in the list from 7 to 10. But if you believe that machine learning is just a subcategory of statistics or if you want to call it statistical learning then all 10 are relevant.
Summary: This is a great article that does machine learning from scratch. This is a fantastic exercise for anyone learning machine learning and Python.