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This repository includes math explanations and code for three different projects I built while self-studying probability theory from Harvard's Stat110 and Stanford's CS109.

First project: Visualizing the convergence of the Geometric Distribution to the Exponential

Second project: Parameter estimation with MLE and MAP and Logistic Regression from scratch

Third project: Markov Chain Monte Carlo and the Metropolis-Hastings Algorithm


I wrote all the code and text included in the MiniProjects directory without LLM assistance. However I did use an LLM to help me understand the connections between Markov Chains and Monte Carlo during my third project. It also helped explain some parts of the theorem I cited in the Metropolis-Hastings derivation.

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Three projects that explain different topics in probability theory

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