Pinned Repositories
2020-Voter-Prediction
Classification using Random Forest and Gradient Boosting Techniques
Automobile-Image-Classification
Computer Vision - Image Classification using Convolution Neural Networks.
Bayesian_Computing_Final_Project
Final project for Bayesian Computing at GWU.
DATS_6202_Final_Project_Group4
Final project for GWU DATS 6202 (Machine Learning I).
Facebook_Data
GWU-Capstone-NBA-Betting
For my capstone project and Master's thesis at George Washington University, I predicted NBA games and deployed betting strategies with real life betting odds. Through extensive feature engineering and model testing, I found what information was most valuable. Ultimately, I used Python libraries such as pandas, numpy, sklearn, and tensorflow.
NBA-Predictions-2020-Restart
Simulate and predict the NBA regular season and playoffs as the 2019-2020 season resumes.
NFL-Salary-Model
Study salary distribution in NFL and model mathematically.
NFL_Play_By_Play
Analyze NFL Play-by-Play data.
GLUE-Benchmark-Group-Project
This repository contains different models that were trained and tested on the GLUE Benchmark tasks. This benchmarks consists of 11 different natural language understanding tasks, including sentiment analysis, textual entailment, question-answering, and more!
dparmar16's Repositories
dparmar16/NFL_Play_By_Play
Analyze NFL Play-by-Play data.
dparmar16/NBA-Predictions-2020-Restart
Simulate and predict the NBA regular season and playoffs as the 2019-2020 season resumes.
dparmar16/NFL-Salary-Model
Study salary distribution in NFL and model mathematically.
dparmar16/Bayesian_Computing_Final_Project
Final project for Bayesian Computing at GWU.
dparmar16/DATS_6202_Final_Project_Group4
Final project for GWU DATS 6202 (Machine Learning I).
dparmar16/Facebook_Data
dparmar16/GWU-Capstone-NBA-Betting
For my capstone project and Master's thesis at George Washington University, I predicted NBA games and deployed betting strategies with real life betting odds. Through extensive feature engineering and model testing, I found what information was most valuable. Ultimately, I used Python libraries such as pandas, numpy, sklearn, and tensorflow.
dparmar16/Flask-Exploration
dparmar16/Gmail-Export
Explore data exported from gmail.
dparmar16/kaggle_titanic
Solution to Kaggle's Titanic problem
dparmar16/M2M-April-Mini-Projects
Use publically available political data to do quick-fire analysis.
dparmar16/Medicare-Hospital-Spending
Comparing hospital expenditures by hospital for different treatments.
dparmar16/Ohio-Voter-File-Visualization
Use publicly available data to generate cross-tabs.
dparmar16/Open-Water-Swimming
dparmar16/Political-Text-Messages
dparmar16/Senate-Dimensional-Analysis
Analyze the political positions of US senators in a geospatial method.
dparmar16/stop-consolidation
Proof-of-concept for optimized stop consolidation