Machine Learning Classifier Project
This project focuses on developing a robust machine learning classifier for image recognition tasks. The classifier is designed to categorize various objects in images with high accuracy and efficiency.
Project Overview
- Implemented a convolutional neural network (CNN) architecture
- Utilized transfer learning techniques with pre-trained models
- Achieved 95% accuracy on the test dataset
- Optimized for real-time classification on edge devices
Technologies Used
- Python
- TensorFlow
- Keras
- OpenCV
- NumPy
Key Features
- Multi-class classification capability
- Data augmentation for improved generalization
- Fine-tuning options for specific use cases
- Exportable to TensorFlow Lite for mobile deployment
Future Improvements
In the next phase of this project, I plan to implement:
- Advanced data preprocessing techniques
- Ensemble methods for higher accuracy
- A user-friendly web interface for demo purposes
For more information or to collaborate on this project, please contact me.