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Introduction to Optimization Algorithms to Compress Neural Networks

Introduction to Optimization Algorithms to Compress Neural Networks

tinyML via YouTube Direct link

Knowledge distillation

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Knowledge distillation

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Classroom Contents

Introduction to Optimization Algorithms to Compress Neural Networks

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  1. 1 Introduction
  2. 2 Local Meetup
  3. 3 What is tinyML
  4. 4 Quantization
  5. 5 Knowledge distillation
  6. 6 Pruning
  7. 7 Pruning techniques
  8. 8 Pros and cons
  9. 9 Lowend factorization
  10. 10 Fast convolutional
  11. 11 Selective attention network
  12. 12 Summary
  13. 13 Questions
  14. 14 General use cases
  15. 15 Pruning whole channels
  16. 16 Conclusion

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