Mathematics for Machine Learning with Python- CST284 KTU Minor - Dr. Binu V P -9847390760

Linear algebra is a field of mathematics that could be called the mathematics of data. It is undeniably a pillar in the field of machine learning, and many recommend it as a prerequisite subject to study prior to getting started in machine learning. I recommend a breadth- rst approach to getting started in applied machine learning. I call this approach a results- rst approach. It is where you start by learning and practicing the steps for working through a predictive modeling problem end-to-end (e.g. how to get results) with a tool (such as scikit-learn and Pandas in Python). This process then provides the skeleton and context for progressively deepening your knowledge, such as how algorithms work and eventually the math that underlies them. After you know how to work through a predictive modeling problem, let's look at why you should deepen your understanding of linear algebra. You should understand the following concepts thoroughly also how these are implemented using pytho