Machine Learning : Complete Maths for Machine Learning

Congratulations if you are reading this. That simply means, you have understood the importance of mathematics to truly understand and learn Data Science and Machine Learning. In this course, we will cover right from the foundations of Algebraic Equations, Linear Algebra, Calculus including Gradient using Single and Double order derivatives, Vectors, Matrices, Probability and much more. Mathematics form the basis of almost all the Machine Learning algorithms. Without maths, there is no Machine Learning. Machine Learning uses mathematical implementation of the algorithms and without understanding the math behind it is like driving a car without knowing what kind of engine powers it. You may have studied all these math topics during school or universities and may want to freshen it up. However, many of these topics, you may have studied in a different context without understanding why you were learning them. They may not have been taught intuitively or though you may know majority of the topics, you can not correlate them with Machine Learning. This course of Math For Machine Learning, aims to bridge that gap. We will get you upto speed in the mathematics required for Machine Learning and Data Science. We will go through all the relevant concepts in great detail, derive various formulas and equations intuitively. This course is divided into following sections,Algebra FoundationsIn this section, we will lay the very foundation of Algebraic Equations including Linear Equations and how to plot them. We will understand what are Exponents, Logs, Polynomial and quadratic equations. Almost all the Machine Learning algorithms use various functions for loss measurement or optimization. We will go through the basics of functions, how to represent them and what are continuous and non-continuous functions.CalculusIt is said that without calculus and differential equations, Machine Learning would have nev