Description : This project is an Express.js-based backend server application that provides user registration and login functionality. It utilizes various libraries such as express, cors, body-parser, and dotenv to handle HTTP requests, enable cross-origin resource sharing, parse request bodies, and manage environment variables. The project also includes external dependencies like crypto-js, shuffle, murmurhash-js, and argon2 for cryptographic operations and data manipulation
Techstack used: React
Libraries used : Express.js, CryptoJS, murmurhash-js, argon2, dotenv
Description : This web application utilizes Python and the Streamlit framework to analyze and explore data from various Olympic Games. The goal of this project is to provide insights into the history, performance, and trends of different countries, athletes, and sports.
Techstack used: Python, Jupyter
Libraries used : Streamlit, Pandas, Plotly Express, Matplotlib, Seaborn
Description : This project is focused on building a movie recommender system based on different genres. The dataset used in this project is derived from IMDB 5000 Movie Dataset, which comprises data of 5000 movies, in which there 28 columns having information such as Movie name, Director name, Actors name, Genre, Movie title, Movie rating and etc.
Techstack used: Machine Learning Python, Jupyter
Libraries used : Streamlit, Pickle, Pandas