How I learned Mathematics for Machine Learning

About me

I am a Software Engineer with extensive enterprise software development experience in both windows and Linux. My primary language has been C++, C++111 apart from Javascript, .NET, Java and Python.

Why I wanted to learn Mathematics for Machine Learning

I wanted to get into Machine learning and eventually develop my own machine learning algorithms. So i had to understand it from a very low level and so i set about learning the mathematics behind it.

How I approached learning Mathematics for Machine Learning

I took up courses on MIT Edx and Coursera but found it very exhaustive. So i also took help from 3blue1brown to get a very good basic foundational understanding of calculus and Linear Algebra apart from Neural networks.

Challenges I faced

The main challenge is if you are not really familiar with mathematics. But if you have some basic High school math knwoedge then its pretty easy with enough time and effort.

Key takeaways

Understanding the math will help me in other fields and topics as well. Because Calculus, Linear Algebra and Probability are few of the fundamental mathematics subjects out there and having a solid foundation on them will go a long way in overcoming any scientific field.

Tips and advice

I suggest you start with the 3blue1brown series of videos on youtube and then eventually do a qucik overview of Mit Edx courses. And eventually if you want to add rigor to your education i suggest you take Khan Academy courses on these subjects.

Final thoughts and next steps

Next step for me is to add some rigor by taking the MIT OCW lectures in depth and solving their example problems.