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Model Compression

Data / Training / Evaluation

Reducing model size and complexity.


Model compression reduces the size and computational cost of neural networks while preserving accuracy.

  • Techniques: Pruning, quantization, knowledge distillation.
  • Applications: Mobile AI, embedded systems, edge devices.