Table of Contents

  1. Introduction
  2. ML/DL Terms and Concepts
  3. Deep Instrumentation
  4. Kelp.Net Reference
  5. Loading and Saving Models
  6. Model Testing and Training
  7. Sample Deep Learning Tests
  8. Creating Your Own Deep Learning Tests
  9. Appendix A: Evaluation Metrics
  10. Appendix B: OpenCL