In which we investigate K-means clustering, a common unsupervised clustering technique for analyzing data.
We discuss support vector machines, a very powerful and versatile machine learning model.
I describe Naive Bayes, a commonly-used generative model for a variety of classification tasks.
I describe logistic-regression, one of the cornerstone algorithms of the modern-day machine learning toolkit.
I describe the basics of linear regression, one of the most common and widely used machine learning techniques.
A discussion of the most important skills necessary for being an effective machine learning engineer or data scientist.