Developed a Machine Learning model using Logistic Regression, SVC, KNeighbors, Decision Tree, Random Forest, and Gradient Boosting Classifiers to predict heart disease. Trained on a Kaggle dataset and evaluated using performance metrics. The code is clear, well-documented, and follows best practices. Know more

Car damage detection using CNN involves training a Convolutional Neural Network to identify and classify vehicle damage from images. This automated system enhances accuracy and efficiency in assessing damage, aiding insurance claims and repair processes by detecting patterns like dents, scratches, and structural issues.Know more

E-waste includes discarded electronic devices, posing environmental and health risks. AI enhances e-waste management through detection, sorting, and recycling. Using computer vision and CNNs, AI identifies and classifies e-waste from images or videos. AI-powered systems enable efficient sorting in recycling facilities. Know more

Efficient password management system, simplifying finance basics for better money management, enhancing self-improvement through effective time management and networking, and developing an AI assistant chatbot that provides human-like interaction, information, and task automation to improve productivity and user experience.Know more