Personal Notes

My most recent passion project has been an 18-month-long deep-dive into measure-theoretic probability.

• Conditional Exkebtations (Latest Big Update: 26-01-20)

As with most things in life, with new information we re-assess. Learning probability has led me to re-evaluate a lot of ideas that were incorrectly presented to me in CS229, on which my Machine Learning notes are based:

• Introduction to Machine Learning (Latest Big Update: 26-01-20)

Other notes I’ve compiled in the past include:

• Introduction to Python & Algorithms
• Introduction to Data Science

Here is a link to a tutorial for Getting Started With \(\LaTeX\) by cnguyen-uk.

University

• MA231 Vector Analysis (Revision Guide)
  Distributed by the Warwick Maths Society in the 2016-2017 academic year, this guide covers multivariable calculus and complex analysis.

• ST202 Stochastic Processes
  These notes introduce random walks, branching processes and formalise Markov Processes, following the course I took at Warwick.

• 7CCM327BT MSc Topology
  Used at King's College London by Prof. Igor Wigman during both the 2017-18 and 2018-19 academic years, this document covers point-set topology (continuity, connectedness, compactness) and serves as an introduction to algebraic topology (fundamental groups). At least 100 students have made use of it so far.

I also leave here my Master's dissertation on Pseudodifferential Operators and the Atiyah-Singer Index Formula in case anybody's curious.