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-

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**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-

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**Importance of Math in Machine Learning**

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.**Mathematics helps you to identify

**under-fitting and over-fitting**by understanding the**Bias-Variance tradeoff.**You can choose

**parameter settings and validation strategies**with the help of math.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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