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RespireNet is an innovative web-based application that harnesses the capabilities of deep learning and Mel-frequency cepstral coefficients (MFCC) as a feature extraction technique for accurate respiratory disease prediction. The primary objective of this user-friendly web application is to facilitate early detection.
The Ruby on Rails Budget-app project is aimed at creating a mobile web application that enables budget management, including user registration and login for data privacy, the introduction of new transactions linked to categories, and the display of expenditures per category.
This is a Server-side Rendering application (SSR) following the MVC architecture. After the user logs in, them can create or edit recipes, adding or removing ingredients, generating shopping list and sharing their recipes with all other users.
Established web app employs Python's Flask Framework for frontend structure, linking with a backend ML model to classify disease types in potato plants based on leaf images and the application of Convolutional Neural Networks.
AlphaGomoku - Play Gomoku Against AI Powered by AlphaZero
Discover unparalleled online shopping on SportsMall, a cutting-edge e-commerce platform built on the robust MERN stack. Dive into a wide array of products, optimize user profiles, monitor orders, and take advantage of extensive admin capabilities. Transform your retail experience with our state-of-the-art MERN technology and interactive interface.
Inhouse Internship Project to develop CO-PO Attainment System for PICT IT Department
This Ruby on Rails project is about building a mobile web app where the user can manage his budget. Them will provide list of transactions associated with a category.
This projects helps you to translate the natural language into the SQL query.
Exemplo simples de autenticação e autorização baseada em tokens JWT.
The "Cyberbullying Tweet Detection" project looks into the world of machine learning to tackle the essential problem of cyberbullying detection in online communication. This project focuses on the creation and implementation of cutting-edge machine learning models to automatically recognize and categorize tweet content containing cyberbullying.
Dashboard for the story of palestine
Tailscale VPN on PaaS hostings such as railway, render, back4app and etc.
Poker Pulse is a companion app designed for poker players participating in live tournaments in Las Vegas. The app allows players to manage their profiles, track tournament schedules, and receive real-time updates. This ensures that players stay organized and informed throughout their playing experience.
A full-stack review-based web application for campgrounds
This project is a comprehensive platform designed to streamline the organization and management of photography events. Whether you're an event organizer, photographer, or attendee, our site offers a seamless experience for browsing, registering, and showcasing photography events.
A repository for an online book store application, featuring frontend and backend code for browsing, searching, and purchasing books.
Flask Database driven web application
Real-Time-Chat is a MERN Stack Chatting App. Uses Socket.io for real time communication and stores user details in encrypted format in Mongo DB Database.
Web application that allows users to search and view dog images based on HTTP status codes.
An Ecommerce website build on MERN Stack.
ecommerce site with multiple functionality
My first open source LLM API deployment - BritneyBot!
Express.JS HTTP server for RemCat app
This project is a dynamic one-page website built with React. It features a customizable banner with a countdown timer, controlled via an internal dashboard. The banner can be toggled on/off, and its content, timer, and link can be updated through the dashboard. All settings are stored in a MySQL database, ensuring persistent and flexible managemet
Start your journey with InnVite and make hotel booking hassle-free.
RecessionAnalysis with Prediction uses data-driven approaches to understand and forecast economic downturns. Through statistical models and machine learning, it analyzes historical trends and equips stakeholders with valuable insights for informed decision-making in uncertain times.
This project uses machine learning algorithms (Random Forest Classifier and Decision Tree) to predict student placement likelihood based on age, gender, CGPA, internships, and backlogs. It provides actionable employability insights, aiding career planning. A user-friendly Flask web app will be deployed on Render for broad accessibility.