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hetankevin's Projects

chicago-traffic-accidents icon chicago-traffic-accidents

Analysis of traffic accidents in Chicago in 2019. Density-based heatmaps of accidents (way more now). Unlike most of the notebooks here, this one's done in R.

copulas icon copulas

A professor I wanted to do research with asked me to read up on copulas before an interview. I ended up doing a bit more than just reading. This is based off the work of Thomas Wiecki (https://twiecki.io/blog/2018/05/03/copulas/).

eda-tutorial icon eda-tutorial

A quick resource put together for a club meeting, as a dummy's guide to exploratory data analysis, clustering and dimensionality reduction.

edward icon edward

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

english-125-literature-review icon english-125-literature-review

My English GSI kindly allowed me to turn in my third paper in the form of a Jupyter Notebook, so here we are. We have a literature review on ToMATo clustering. Citations can only be seen with the cite2c extension, but I've managed to screenshot the notebook and upload it as Assignment3.jpg

feature-ntk icon feature-ntk

Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

geomvae icon geomvae

Trying to find a geometric interpretation of the output of the encoder side of a VAE trained on Mario worlds 1-1, 1-2, 1-3.

mariorl icon mariorl

Reinforcement learning, module as part of a larger project with the aim of using this as a confirmation that a generated Mario level is playable.

mixmc icon mixmc

Learning Mixtures of Continuous-Time Markov Chains

mlfinlab icon mlfinlab

MlFinlab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

pairstrading icon pairstrading

Repository containing the code for a pairs trading investment strategy (Master Thesis in Electrical and Computer Engineering - Técnico Lisboa).

schedule-opt icon schedule-opt

Daniel and I were trying to save UM students from bad schedule decisions, but realized that we were in over our heads here. It's a huge, huge tree of prerequisites that we don't have the data for. Instead, here we have two optimization heuristics (hill climbing and simulated annealing), the core of the project, written in Python.

senator-filings icon senator-filings

Scrape public filings of the buy + sell orders of U.S. senators and calculate their returns

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