Projects

A smart shared accommodation platform tailored for the Indian market. BharaGhar simplifies room rentals with verified listings, roommate matchmaking, and intelligent filters for affordability, location, and preferences. Built with a FastAPI backend, it focuses on trust, convenience, and a seamless user experience for students and working professionals. (Codes are in private repo currently)

A minimal and efficient note-taking web app designed for students and productivity-focused users. Built using FastAPI, MongoDB, and Bootstrap, helloNotes allows users to create, organize, and manage their notes seamlessly. With a focus on speed and simplicity, it supports rich-text formatting, secure storage, and easy retrieval—making note-taking effortless and accessible from any device.(Codes are in private repo currently)

A predictive analytics tool that leverages historical market data and machine learning to forecast cryptocurrency trends. CryptoForecast helps users make informed investment decisions by providing future price predictions, volatility analysis, and trend visualizations. Designed with a focus on accuracy and usability, it empowers both new and seasoned investors to navigate the crypto market with confidence.

A productivity-focused Chrome extension that tracks your browsing behavior and encourages positive habits through a points-based reward system. Built with JavaScript and the Chrome Extension API, BrowseBetter monitors website usage in real-time, helping users stay accountable and focused. It gamifies self-discipline by assigning scores based on browsing patterns, making habit-building fun and measurable.

An end-to-end data analysis project focused on uncovering patterns in customer behavior, sales trends, and product performance from an e-commerce dataset. The project involved data cleaning, exploratory data analysis (EDA), and visual storytelling to generate actionable business insights. Additionally, machine learning techniques like XGBoost were used to predict customer purchase behavior and identify high-value products.

AttriPredict is a web-based machine learning tool designed to predict employee attrition with over 80% accuracy. Developed using Random Forest and integrated with a Flask interface, it enables HR teams to input employee data and receive real-time risk predictions. The project combines EDA, feature engineering, and visualization to identify key factors driving attrition, supporting data-driven retention strategies..