Developed a real-time sign language detection system using computer vision and deep learning. The model translates sign language gestures into text, improving communication accessibility.

Developed a smart traffic signal system using OpenCV and machine learning to analyze real-time vehicle flow, predict traffic congestion, and dynamically adjust signal timings. This system improved traffic flow efficiency by 50% by minimizing wait times.

Built a web-based platform for custom-fit clothing using AI-powered body measurement technology. The system uses computer vision and deep learning models to analyze body shapes from images, achieving a 25% improvement in tailoring accuracy.

Developed an AI-powered task optimization system that suggests tasks based on real-time emotion detection. The system uses a webcam to capture facial expressions and DeepFace to analyze emotions, achieving an emotion detection accuracy of over 90%.

Log workouts, track nutrition, set goals, and monitor progress to stay fit and motivated!

A machine learning-based project that suggests personalized courses using Coursera dataset analysis. It leverages content-based and collaborative filtering techniques to provide accurate recommendations.

Uses OpenCV, Deep Learning, and TensorFlow to detect faces and mark attendance automatically. This project helps automate attendance tracking with high accuracy and real-time detection.

A student-led initiative to connect skills with service. This platform empowers volunteers to contribute their technical, creative, and social talents toward meaningful community impact.

A collection of machine learning projects and experiments, exploring algorithms, data preprocessing, model building, and performance evaluation.

A platform for developers to practice DSA, track progress with leaderboards, learn via quizzes, and connect in a forum.