For my Sentiment Sphere capstone, I developed a web-based dashboard that analyzes sentiment across user-provided text and files, YouTube comments, Bluesky content, and finance data. It categorizes results as positive, negative, or neutral.
I used Python, FastAPI, Pandas, and NumPy for the backend, with React, Tailwind CSS, Axios, and Recharts for the frontend. The project also used the YouTube Data API v3, Bluesky AT Protocol, Alpha Vantage API, and yFinance.
As a Trainee Intern in the HCL Internship and Training Program via MIT ADT University, I completed AI with LLM training. My learning included Python libraries, machine learning and deep learning fundamentals, NLP, LLMs, RAG, and AI ethics.
