Projects

Sentiment Analysis AI

Technologies: Python, PyTorch, NumPy, CUDA

  • Created NLP for sentiment analysis of 10 GB of X (Twitter) posts, leveraging CNN and transformer architectures achieving 92% accuracy
  • Leveraged CUDA to dramatically accelerate the training of deep learning models, cutting training time by 100×
  • Implemented custom data preprocessing pipelines, improving model accuracy by 20%
Wackypedia

Technologies: Python, Selenium, React, Flask, Firebase

  • Produced a full stack application using Python, Selenium, Flask, React, and Firebase
  • Streamlined the collection of over 2,000 low-traffic Wikipedia sites using a Selenium web scraper
  • Capability to scrape more than 3,000 unique sites per hour, significantly improving data acquisition efficiency