This summer I took a fascinating course — Machine Learning for Trading. For those who don’t know me, I’m pursuing my Master’s in Computer Science with a specialization in Machine Learning. Every semester, I like to reflect on what I’ve learned and share it in an abstract yet informative way. If you have even a little familiarity with Machine Learning and math concepts, you’ll find this article easy to follow.
I’m 25 now. Looking back, my sense of sports didn’t develop particularly early in my life. There were, of course, childhood games such as hide-and-seek, seven stones, blindfold, and many more. But these won’t be counted as real sports. At least they weren’t for me. Then, after a few years, we started playing gully cricket, badminton, and some basic version of football, all perhaps until 4th-5th standard.
If you’ve ever worked with deep learning models and, like me, wondered how machine learning libraries like TensorFlow and PyTorch handle large neural networks so efficiently, this blog is for you.
First things first, have you heard of Knowledge Graphs before? Not asking if you know what it is, just if you overheard someone talking about it or casually read the term somewhere. If yes, amazing! If no then also amazing because we will go through it in as demystified way as possible.