A dual-system AI solution for farmers: one module identifies crop diseases via deep learning (CNN), while another provides crop recommendations using environmental and soil parameters. Deployed as a real-time web application.

This project focuses on detecting fake news articles using NLP techniques and machine learning. Achieved 96% accuracy and 0.97 ROC-AUC using a Random Forest classifier with SMOTE for class balancing.

SkillWeave is a dynamic freelancing platform connecting skilled professionals with job opportunities. I led the team in developing the project, integrating real-time communication with WebSocket.io, and implementing payment functionality using Razorpay. The platform features an innovative self-made chatbot for enhanced user interaction.

Q-buster is a campus food ordering platform designed to streamline food orders within a campus setting. I developed the project using React.js, ensuring a seamless and user-friendly interface. The platform integrates real-time notifications and budget tracking features.

This project involves predicting stock market trends using machine learning techniques. I built a predictive model using LSTM networks and developed an interactive dashboard with Streamlit to visualize stock predictions and trends.

Bennett-e-Dorm is a hostel management system designed to streamline room allocation and administrative tasks. I implemented the project using C++ and utilized a Binary Search Tree for efficient room allocation and management.

Retail Radar predicts product sales using advanced machine learning techniques. The project integrates data cleaning, feature engineering, and ensemble models to help retailers optimize inventory and boost operational efficiency.