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.
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.