Fastest YOLOv5 CPU Inference with Sparsity and DeepSparse with Mark Kurtz

Discover the fastest CPU inference for YOLOv5 models with Mark Kurtz, Director of Machine Learning at Neural Magic! 🚀 In this video, Mark delves into the world of sparsification and its transformative impact on YOLOv5 models. Learn about Neural Magic's DeepSparse engine and how it brings GPU-class performance to commodity CPUs.

Key topics covered:
Introduction to sparsification: algorithms, techniques, and motivations
Performance improvements with YOLOv5 sparsification
Sparse transfer learning and project-based sparsification
Deploying models with the DeepSparse inference engine
Exporting models to ONNX format and running with DeepSparse
Quantization techniques for reducing precision and compute needs

Discover the impressive results of sparsification, including up to 7x faster latency, 12x faster throughput, and 13x smaller file sizes. Mark explains how to apply sparse transfer learning to fine-tune models on custom datasets, keeping architectures efficient while maintaining high accuracy.

Don't miss out on the next steps, including updates to YOLOv5 and YOLOv5 P6 models and upcoming research on knowledge distillation techniques. This video is a must-watch for anyone looking to optimize and deploy YOLOv5 models on CPUs.

🔗 Explore more:
Ultralytics HUB: https://www.ultralytics.com/hub
YOLOv5 Docs: https://docs.ultralytics.com/models/y...
Deploying YOLOv5 with DeepSparse: https://www.ultralytics.com/blog/depl...
About Neural Magic: https://www.ultralytics.com/about

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#YOLOv5 #Sparsification #DeepSparse #NeuralMagic #Ultralytics #AI #ComputerVision #MachineLearning #YOLO #ModelOptimization #CPUInference