Project Overview
Deep learning model for image classification using TensorFlow. Achieved 95% accuracy on test dataset.
Key Features
- Custom CNN architecture
- Data augmentation pipeline
- Real-time inference capabilities
- Model performance analysis tools
Technical Challenges
Optimizing the model architecture to achieve high accuracy while maintaining reasonable inference times was a significant challenge.
Key Learnings
Deepened understanding of CNN architectures, data preprocessing techniques, and model optimization strategies.