Maintained ReactJS frontend and created new web pages for internal use. Connected frontend to Supabase to display information that can be readily updated.
Used BeautifulSoup to scrape prior match data and predict the results of future matches using a Random Forest Model in the Sci-Kit Learn library. Achieved 70% accuracy.
Analyzed over 500,000 customer complaints using Pandas at my Internship for Citi. Ran sentiment analysis on each review using NLTK for preprocessing and an LGBM model to analyze the data.
Created an android app allowing students to place food orders for other students to deliver made with Flutter and Firebase for a high school midterm project alongside a partner.
