Table of Contents

1. Introduction
2. Business problem
3. Mapping to Deep Learning problem
4. Data Set Used
5. Model Architecture
6. Loss Function
7. Implementation Overview
8. Building data pipeline
9. Defining model architecture
10. Defining loss and accuracy functions
11. Defining Step function
12. Final flow
13. Validating results
14. Understanding Deployment
15. Future Work & Conclusion
16. References

#data-science #machine-learning #tensorflow #deep-learning #image-similarity