Projects

Writing cover letters during a job search can be a time-consuming and challenging task, requiring job seekers to carefully articulate their skills, experiences, and motivations for each role. This application streamlines the process by allowing users to quickly generate personalized cover letters that effectively communicate their qualifications. By leveraging AI-powered language models, the app helps transform raw thoughts and past experiences into a well-structured, compelling, and tailored cover letter. With features like resume-based querying, iterative editing, and intelligent keyword extraction, users can ensure that their application highlights the most relevant aspects of their background, making the job application process more efficient and impactful.

Technologies:

• Retrieval Augmented Generation (RAG)
• LangChain
• OpenAI API
• DeepSeek-v3 LLM
• ChromaDB Vector Database

An application that provides a bias-free method to analyze happiness scores via advanced data mining techniques including OPTICS and DBSCAN.

Analyzed data for 156 countries across 8 years to extract the most significant factors and derive a custom metric for public happiness. Additionally, I recommend a combination of factors (see the red arrow in the figure) that would most help a particular country increase their happiness score.

Technologies:

• Time-Series Analysis
• Clustering
• Sci-kit learn
• NumPy
• Streamlit

Psst! For a sneak peak at all of my projects, visit my GitHub profile