Hi! I’m Anirudh Pai,

and I’m a student in U.C. Berkeley EECS.
I first became interested in the STEM field when I went to the San Jose Tech Museum for a school field trip in 5th grade. 

There, I had the opportunity to build my very own robot using nothing but Legos and block code. Working with the I ended up creating a small blue robot designed to maneuver around a room using a combination of infrared and touch sensors. I was immediately enthralled by how a couple simple lines of code could create something so fascinating. From then on, I’ve striven to grasp at every opportunity to delve into the field of computer science and robotics even further.

 
I started by taking a couple of computer science classes in middle school, where I learned how to design websites using HTML and CSS. From there, I self-taught myself other programming languages such as Python using Coursera and Udemy. 

I learned how to create algorithms using different programming techniques such as recursion until I felt as though I needed to try something new—machine learning. 

I tried to self-learn machine learning through Youtube videos, articles, and Udemy courses, but I often found myself getting frustrated because I couldn’t understand the abstract concepts behind some of the more advanced models such as artificial and convolutional neural networks. I found that a lot of the models used advanced mathematical concepts from multivariable calculus and linear algebra. 

Nevertheless, after several tiring months, I felt as though I had finally begun to grasp the ideas behind machine learning. I know that there are other students who are in the same situation that I was in a couple months back, and thus, I created Machine Learning Works, a website where I thoroughly explain different machine learning algorithms and how they can be used in a variety of projects .

My mission is to inspire other students by introducing them to fascinating machine learning concepts in simple and fun ways.