When it comes to learning math for machine learning, most of us stuck and don’t know what to learn and from where to learn…Right?.

That’s why I thought to write an article on this topic. In this article, I’ll discuss how to learn math for machine learning step by step. So read this article and clear your all confusion regarding math for machine learning.

Now without further ado, let’s get started-

How to Learn Math for Machine Learning?

Before learning math, you should know why math is important for machine learning and why you can’t avoid math. Alright…?. So let’s understand the importance of math in Machine Learning-

Importance of Math in Machine Learning

1. With the help of mathematics, you can select the right algorithm which includes giving considerations to accuracy, training time, model complexity, number of parameters, and number of features.

2. Mathematics helps you to identify under-fitting and over-fitting by understanding the Bias-Variance tradeoff.

3. You can choose parameter settings and validation strategies with the help of math.

4. Without knowledge of math, you can’t estimate the right confidence interval and uncertainty.

That’s why you should have mathematics knowledge in order to become a Data Scientist or Machine Learning Engineer.

Now you understood the importance of math, so let’s see how to learn math for machine learning and what’s the first step-
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