An introduction to machine learning course with a focus on the K-Nearest Neighbors algorithm. Developed by James Bocinsky.
Please download the PDF to view it: Download PDF.
In order to view the lectures and run experiments you will need to have python 3+ and jupyter notebooks installed on your machine. If you do not have these already I suggest you Download Anaconda which has both of these and many other useful python packages already in it.
To view a lecture you will boot jupyter notebooks and browse to the lecture folder and open it. Then you can see the lecture content and begin learning about K-Nearest Neighbors. Make sure to view the student version of each lecture so you don't see the solutions before you begin an exercise.