FULL STACK DEVELOPER | MERN | SQL | AI-ML SPECIALIZATION | MOBILE-APP DEVELOPER
Hire MeI'm a passionate MCA student at DMIHER, with strong skills in MERN stack, SQL/NoSQL DBs, With practical experience of using AI AND ML tools-techniques and DevOps tools. I love building impactful apps and solving real-world problems.
HTML5
JavaScript
React
MySQL / MongoDB
Python
BootStrap
Android Development
Node.js
Git
Docker
AWS
CSS3
Login/Register app using React, Node, MongoDB with JWT, bcrypt, and role-based access.
Weather forecast app using OpenWeatherMap API with real-time data and location support.
A responsive restaurant landing page with menu, order now section and animations using Bootstrap.
A form validation project using HTML, CSS, and JavaScript to ensure user input is correct and complete.
An interactive admin dashboard for managing orders, products, and analytics using React and Chart.js.
A browser game to test your reaction speed using JavaScript, DOM manipulation, and timers.
A full-featured task manager built with MERN stack. Add, update, and delete your daily tasks efficiently.
Runs the DeepSeek-1.5B model completely offline ensuring data privacy with no cloud dependency. Built with Node.js (Express) backend and custom HTML/CSS frontend. Features: clean UI, smooth animations, typing indicators. Tested APIs using Postman and cURL for end-to-end validation
A computer vision project built with Python, TensorFlow, OpenCV, and Jupyter Notebook for detecting face masks in real-time video streams.
A cutting-edge AI trading bot using Reinforcement Learning (PPO) and LSTM to predict NIFTY movements and automate option trading decisions. Built with Python, Stable-Baselines3, Gym, and yFinance.
A voice-controlled AI assistant built with Python, speech recognition, and text-to-speech. It performs web searches, sends emails, and automates daily tasks efficiently.
A live-option trading bot built with Python that processes real-time market data, implements multiple trading strategies, and sends instant trade alerts via a Telegram bot.
An LSTM deep learning model trained on 28 years of NIFTY data (1996–2024) using technical indicators like RSI, CCI, Bollinger Bands, and MA. Achieved 88% accuracy in predicting UP, DOWN, and SIDEWAYS market signals.
A full-stack real-time chat application built using Node.js, Express, Socket.IO, and MySQL. Features include user authentication, group chat, and message persistence with MySQL. Deployed locally with secure database integration.
Feel free to download my resume to know more about my education, skills, and project experience.
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