Policy Plotter – R Shiny Application: Solved a core problem facing the Federal Reserve Board by independently developing a plotting application to vastly increase the efficiency of creating charts/exhibits for The Federal Open Market Committee (FOMC). This committee determines monetary policy for the entire United States. I automated the process of chart creation which draws focus away from data and code integrity.

repeat-sales-model-using-distributed-computing

Forecasting corporate bond returns with a repeat sales model on 72 distinct billion item matrices ~ 1TB.

space-optimized-computer-vision

A space optimized CNN developed through synchronous distributed training, weight pruning, and quantization in Vertex AI on GCP

string-similarity-custom-functions

Text Classification: Fast, custom string similarity functions in Python mapping lambda functions to NumPy arrays, assigning issuers to one of 10,000 classes.

umass-senior-project-2019

The purpose of my application was to solve a problem many businesses (small businesses in particular) face. They do not know how much to produce, where to price, how much to spend on advertising and many other questions. Eden’s purpose was to answer these questions for them easily and with no technical acumen required by the user. Eden would model supply and demand equations using ordinary least squares (OLS) regression on the user’s data to form the best fitting supply and demand equations possible. The best fit was to be ensured by regressing each variable against demand or supply, determine the best shape via the highest adjusted R2, and then do an OLS regression and simplistically tell the user what the results mean. Eden would attempt multiple shapes like linear, logarithmic, cubic, quadratic, and inverse. The user interface would be easy to navigate and user-friendly.

web-scraping-sec-data

Web scraping commercial paper and negotiable certificates of deposit data from the SEC EDGAR public website https://www.sec.gov/edgar/searchedgar/legacy/companysearch.html

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