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Lab for Innovation Science at Harvard data science competition. My solution scored around the top 15. I had planned to try other things, but I used only 1/3 of the allowed competition time -- and hence did not explore advanced feature engineering in the winning solutions. But interestingly, this solution was similar to winning solutions.

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competitive-programming-contests data-science water-quality-modeling

2022-lish-harvard-datasciencecompetition's Introduction

Hi there! ๐Ÿ™‹โ€โ™‚๏ธ

I'm Ryan.

I'm a quantitative ๐Ÿงฎ programmer.

My work spans brain rhythms and temporal representations for solving memory-guided tasks. I have extensive experience in time-series analysis, Bayesian decoding, and emerging statistical sequence models.

I'm planning projects in a few areas

  • communication subspaces with tensor methods :: going beyond pair-wise communication with product spaces
  • successor models with factorized what, where, and policy streams :: extending Eichenbaum's model
  • content-targeted autoencoders :: filtering signals by content

Collabs welcome ๐Ÿค. Let's build something awesome ๐Ÿงจ. Enjoy :)


๐Ÿงฐ Languages and Tools:

Python Julia Terminal vim cpp cpp

2022-lish-harvard-datasciencecompetition's People

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