Notes: Machine Learning

I have been an avid learner as far as statistics and machine learning is concerned. My primary reason for exploring them has been the use-cases cutting across different domains and problems.

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

Machine Learning Basics

Machine Learning Essentials

Case Study : Optimisation (Optrees Package)

Case Study : Interpreting Regression (Basics + Assumptions)

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

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