Machine Learning Notes

My primary reason for exploring Machine Learning has been the ability to apply them to use-cases cutting across different domains and problems.

I have been an avid learner of statistics and machine learning. My primary reason for exploring them has been the ability to apply them to use-cases cutting across different domains and problems. Primary interest though pertains to the market place, trading, pricing, optimisation problems.

I have had the opportunity to explore healthcare, trading and sports analytics in the form of cricket, where I have been able to both formulate and solve a bunch of interesting problems end to end.

Machine Learning Basics

Machine Learning Essentials

Data Science with R (Optrees)

Machine Learning Regression (Interpretation)

In the process, I would often end of re-using similar problem-solving approaches and often wanted to remember all the cool tricks/hacks and hard-learned concepts I have had been able to work-out all these years. Some of these have allowed me to win some interesting competitions as well.

Auquan Financial Time Series

And several other contests during campus days !!

Besides improving your odds of winning these, I decided to write some notes to help collate concepts and takeaways from ML in an intuitive fashion. If you are one of those guys who love diagrams and intuition over maths to better understand stuff, you would love them.

I might have made small mistakes in calculations or derivations and have corrected those wherever possible. Feel free to point them out in the case, you identify them. I have updated the documents in such cases.