Foundations for Machine Learning

Currently Playing: Foundations for ML | Linear Algebra | Linear transformation as Matrix multiplication [Lecture 3]

"Mathematical Foundations for Machine Learning" Linear Algebra is one of the foundational pillars of ML. But how exactly? Machine Learning is full of linear transformations. When you multiply a vector by a matrix, you are simply performing a linear transformation. So what is a linear transformation? Linear transformations change one vector into another. This is exactly what matrix multiplication also does to a vector. The first column of the matrix is the transformed i vector and the second column is the transformed j vector (in 2D). For the past 4 months, I have been working on a course to lay the foundations for ML. I have released this course on Vizuara's YouTube channel titled "Foundations for Machine Learning." This will be a 45-hour course with ~65 lectures. Here is my new lecture that introduces Linear Algebra with an emphasis on its utility for ML published on Vizuara's YouTube channel. I show you how to get an intuition about linear transformations and how to define this transformation as a matrix simply by tracking what happens to the unit vectors i and j. Check this out. I am sure you are going to enjoy: https://youtu.be/W49sCL5Lsxc There are no prerequisites for this course. If you have basic logical thinking capability and a willingness to dedicate time, consistently, you can follow this course. I have tried to simplify the course content as much as possible by trying to give you a logical and geometric intuition rather than only mathematical steps.