A web application that leverages a Genetic Algorithm (GA) to automatically generate optimized timetables for schools and universities addresses the complex and resource-intensive nature of scheduling. Timetabling is an NP-hard problem, involving numerous constraints such as avoiding conflicts in teacher schedules, room capacities, and student preferences.

A student-focused peer-to-peer platform designed for buying and selling used educational materials and facilitating co-living arrangements. Features include integrated chat functionality for seamless negotiation of product sales and shared living arrangements.

CIFAR-10 Image Classification using Transfer Learning involves leveraging pre-trained models to classify images into 10 distinct classes. The dataset consists of 50,000 training images, with 5,000 images per class, and a test set containing 10,000 images.

Basic implementation of a machine translation system from German to English using TorchText and a Sequence-to-Sequence (Seq2Seq) model with Gated Recurrent Units (GRU).

LearnEase is an advanced Learning Management System (LMS) designed to enhance the educational experience through innovative features. It offers Chapter-Wise Course Playback and automatic AI based quiz generation, ensuring a personalized and flexible learning journey.

It predicts Titanic passenger survival using data analysis and machine learning. Key features include 'GenderPlus', 'Family_Size', and 'FamilySurvivalRate'. The model uses XGBClassifier with hyperparameter tuning for robust predictions.

This project showcases a Convolutional Neural Network (CNN) designed for handwritten digit recognition using the MNIST dataset. A custom dataset class enables efficient data handling and augmentation, while the CNN architecture is specifically optimized for digit classification.

The WIFI-based college attendance system leverages a mobile app that incorporates face recognition, location verification, and BSSID verification for secure attendance tracking.