assembly-lab

Coding done for Microprocessor lab (TY Sem 6 2023-24)

catch-a-match

🎉 Welcome to "Catch a Match," where we turn quiz responses into unexpected connections! 🧠 This tool analyzes quiz answers from MKSSS's Cummins College of Engineering For Women to pair participants based on answer similarities. Developed for Gandhaar, our college festival, in collaboration with the Wings Magazine Club. 📚

financial-literacy-website

This project is a financial literacy website designed to educate users on various aspects of personal finance. It includes interactive features aimed at improving financial understanding and decision-making skills.

geniustoylibrary

Forking Genius Toy Library

hire-and-connect

"Hire&Connect" is an Android application tailored for tradesmen (electricians, plumbers, etc.) to exhibit their services, pricing models, and enable user-initiated service bookings. Users can easily explore profiles, evaluate past work, and securely book services, enhancing trust and efficiency in the tradesmen marketplace.

instagram-follow-back-finder

Find out who doesn't follow you back, and who you don't follow back on Instagram. Python script that uses Instaloader library for web scraping.

knight-in-pixel-armour

leetcode-java

LeetCode problems in Python

leetcode-python

LeetCode problems in Python

leetcode150_java

Solved in Java: https://leetcode.com/studyplan/top-interview-150/ (old link: https://leetcode.com/problem-list/top-interview-questions)

leetcode150_python

Solved in Python: https://leetcode.com/studyplan/top-interview-150/ (old link: https://leetcode.com/problem-list/top-interview-questions)

spendwise

This project, developed during NEUEDA's training in collaboration with Citibank, is a Personal Financial Management (PFM) application. SpendWise API helps users manage their finances by enabling budgeting, expense tracking, and financial goal setting. Users can register, login, add transactions, and set budgets with ease.

tejasgadgil

web-dev

webdev-angela-yu

what-would-my-fridge-cook

"What Would My Fridge Cook?" is a machine learning-based tool that recommends recipes based on user-provided ingredients. Utilizing a k-Nearest Neighbors (k-NN) model and implemented in Python with a Tkinter GUI, it helps users discover new recipes by suggesting those with similar ingredient lists.