Austin Emergency Services Complaint NLP
This project utilizes BERT's NLP to categorize complaint descriptions and expose the model in a dashboard interface that allows users to provide a complaint and see how it would be categorized for the City of Austin, Texas and derive insights with those categories. Data was collected from BigQuery Public Datasets
New York State School Dropout Prediction
This project aims to predict dropout rates for specific demographic groups and identify which ones are at higher risk given 117k records collected from the New York State Education Department (NYSED), as of 2024.
Microchip Production Optimization using Linear Programming
This project aims to maximize the weekly profit of a chip manufacturing plant. Given time as a resource to produce a chip, the profit per unit and the cost per unit determine at most 5 products out of 10 to be utilized while maximizing profit.
Determining Price Elasticity of Demand on Retail Products
This analysis applies the concept of Price Elasticity of Demand to one year of UK retail sales data, using regression techniques to measure how price changes affect demand and profitability across products. Insights can guide pricing strategies to improve revenue outcomes.
Coming Soon
Consumer Financial Protection Bureau Dispute Prediction
This project uses BERT-based NLP to encode complaint text and combines it with structured features in a neural network to predict whether a customer will dispute a financial institution’s response to their complaint.
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