Deep Learning & AI Projects

Cross-platform app and web application to detect diseases in plants by scanning leaf images through neural networks. Implemented CNN architecture with transfer learning for accurate disease classification.

Single voice assistant supporting multiple users with personalized results. Achieved 98% accuracy for 3 users with 10 minutes of training data over 10 epochs using speaker identification and NLP.

Deep learning project using CNN and transfer learning with VGG16 model to detect COVID-19 from chest X-rays. Achieved 97.50% accuracy in medical image classification.

Convolutional neural network application recognizing 43 different traffic signs. Implemented for autonomous vehicle applications with 94.45% accuracy.

Ready-to-use Core ML modules for iOS applications using TuriCreate. Developed optimized models for mobile deployment with real-time inference capabilities.

Machine learning model providing product recommendations based on collaborative filtering and user behavior analysis. Implemented matrix factorization techniques for enhanced accuracy.