Nearly all of my CS-related work can be found on my GitHub. I make no promises about correctness as I have not gone back to correct my problem sets and note that everything requires attribution if you use it, so if you happen to use a solution of mine to solve a problem, mention it. Also, cheating sucks and I have told my old professors about putting my homeworks online. What follows below are specific posts related to the courses that I have taken.

## Machine Learning, CS529 Spring 2015

In-depth intro to machine learning - learning theory, neural nets, baysien methods, markov models. Course repo can be found here.

### Related Posts

## Theory of Computation, CS500, Spring 2015

Models of computation, and complexity theory – topics that tend to give me a bit of a headache. Homeworks can be found here

## Data Mining, CS591, Fall 2014

Introduction to data mining techniques, including classification (neural nets, SVMs, decision trees, random forests), clustering (biclustering, hierarchical agglomerative clustering, k-nn), time-series mining, graph mining, and other topics. My final project can be seen here. The course repo with some of the work on it lives here.

## Analysis of Algorithms, CS561, Fall 2014

Great course - covering derivations and mathematical proofs of various algorithms, including some randomized algorithms, dynamic programming, graph algorithms, max flows, linear programming, and NP-completeness/reductions. All of my homeworks are typeset and can be found here.

## Design of Large Programs, CS351

Ludicrous class on software engineering. I have one major project up on GitHub.