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Resource Efficient Machine Learning in a Few KBs of RAM - tinyML Summit 2020
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- 1 Intro
- 2 Compute Spectrum: AI
- 3 Resource-constrained lot Devices
- 4 Requirements on The Edge
- 5 Broad approaches for TinyML
- 6 Edge Machine Learning (EdgeML) - Objectives
- 7 Microsoft's EdgeML Library
- 8 EdgeML Building Blocks
- 9 ProtoNN: Training Algorithm
- 10 Comparison to Uncompressed Methods
- 11 Prediction Accuracy vs Model Size
- 12 FastRNN
- 13 Prediction on Edge Devices
- 14 Time Series
- 15 Conclusions
