According to Wikipedia, the Gram–Schmidt process is a method for orthonormalising a set of vectors in an inner product space, Gram–Schmidt process, Wikipedia Orthonormalising? Not only is it “right,” it also makes your life a whole lot easier. If you don’t believe me, just watch the video on Coursera or have a go at it with … Continue reading Gram-Schmidt

Special Matrices

In Coursera’s Mathematics for Machine Learning: Linear Algebra class, we learned all about matrices. One of my favorite is the row echelon form or REF. I like it ‘cuz it sounds fancy and Trekkie-like. Anyways, we had to write a Python application that converts a 4×4 matrix into row echelon form. There’s also a feature … Continue reading Special Matrices

Pre-work Requirements

Below are courses that we needed to complete prior to the official start date of the class. I’ve included the links so you can check them out! Data Science Math Skills – Mathematics for Machine Learning: Linear Algebra – Basic Statistics – Python for Data Science – Excel Basics – … Continue reading Pre-work Requirements