NeuralFlix

Workshop: How to Optimize Deep Learning Models for Production

Presenter: Mark Kurtz

Topics covered:

1. What model pruning is, including benefits and downsides;

2. SOTA pruning algorithms and techniques that you can implement today;

3. SparseML, an open-source tool that makes pruning easy and successful;

4. Guaranteed ways to get production performance out of a pruned model.

After watching this video, you’ll be able to optimize your NLP and/or computer vision model, apply your own data with a few lines of code, and deploy it on commodity CPUs at GPU-level speeds.

More ML Research in Action Videos

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Workshop: How to Optimize Deep Learning Models for Production
How to Compress Your BERT NLP Models For Very Efficient Inference
Sparsifying YOLOv5 for 10x Better Performance, 12x Smaller File Size, and Cheaper Deployment
Tissue vs. Silicon: The Future of Deep Learning Hardware
Pruning Deep Learning Models for Success in Production

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Workshop: How to Optimize Deep Learning Models for Production