🚀 Interactive Learning Experience
Run these Jupyter notebooks directly in your browser with zero setup. Click any "Launch" button to start coding immediately!
Defect Detection Fundamentals
Build your first CNN-based quality control system from scratch. Learn image preprocessing, model training, and evaluation with real-world examples.
YOLO for Defect Localization
Learn to detect and localize multiple defects in a single image using YOLO architecture. Includes custom dataset preparation and training.
This notebook is currently in development
Unsupervised Anomaly Detection
Discover defects without labeled data using autoencoders and variational methods. Perfect for rare defect types.
This notebook is currently in development
💡 What You’ll Need
No Installation Required
All notebooks run in the cloud. Just click and start learning!
Basic Python Knowledge
Familiarity with Python syntax and basic programming concepts.
Willingness to Learn
Curiosity and enthusiasm for AI and computer vision!
🎯 Learning Path
We recommend following this sequence for the best learning experience:
- Start with Fundamentals → Complete the Defect Detection Tutorial
- Explore Object Detection → Learn YOLO for precise localization
- Advanced Techniques → Master anomaly detection methods
- Build Your Own → Apply knowledge to your specific use case
🤔 Questions?
- 💬 Discussion: Join our GitHub Discussions
- 🐛 Issues: Report problems on GitHub Issues
- 📧 Contact: Reach out at james@detectdefects.com
Ready to Build Something Amazing?
These notebooks are open-source and free to use. Star us on GitHub if you find them helpful!
View on GitHub