Deep Learning Booklet
Last updated on 2015-07-17
About the Book
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- What is H2O?
- Deep Learning Overview
H2O’s Deep Learning Architecture
- Summary of Features
- Training Protocol
- Advanced Optimization
- Loading Data
- Additional Parameters
Use Case: MNIST Digit Classification
- MNIST Overview
- Performing a Trial Run
- Web Interface
- Grid Search for Model Comparison
- Checkpoint Models
- Achieving World Record Performance
- Nonlinear Dimensionality Reduction
- Use Case: Anomaly Detection
- Appendix A: Complete Parameter List
- Appendix B: References
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