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Meetup: CPU Accelerated Fine-Tuning for Image Segmentation using PyTorch

SusanK_Intel1
Employee
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Want to learn how to accelerate fine-tuning models on your CPU using PyTorch?

View the video replay of the Houston Machine Learning Meetup, March 4, 2023 titled: 
CPU accelerated fine-tuning for image segmentation using PyTorch.

Abstract

PyTorch delivers great CPU performance, and it can be further accelerated with the Intel® Extension for PyTorch* (IPEX). In this tutorial, Ben Consolvo, AI Solutions Engineering Manager at Intel, will walk you through a real-world example of training an AI image segmentation model using PyTorch 1.13.1 (with ResNet34 architecture); the model will learn to identify roads and speed limits from satellite images, all on the newly released 4th Gen Intel® Xeon® Scalable Processor (Sapphire Rapids). You can find the code to this example on the IPEX GitHub repository here.

Thanks to Yan Xu for the opportunity to present at the Houston Machine Learning March meeting!

We encourage you to learn more about and incorporate Intel’s other AI/ML Framework optimizations and end-to-end portfolio of tools into your AI workflow. Also, visit AI & ML page to learn about Intel’s AI software development resources to prepare, build, deploy, and scale AI solutions.

For more details about the new 4th Gen Intel® Xeon® Scalable Processors, visit AI Platform where you can learn about how Intel is empowering developers to run end-to-end AI pipelines with Intel® Xeon® Scalable Processors.

About our expert

Ben Consolvo Portrait - FINAL.jpg

Ben Consolvo, AI Solutions Engineering Manager at Intel

Ben has been building a team and a program around Intel’s AI technology paired with Intel’s HW offerings. He brings a background and passion in data science, particularly in deep learning (DL) and computer vision. He has applied his skills in DL in the cybersecurity industry to automatically identify phishing websites, as well as to the oil and gas industry to identify subsurface features for geophysical imaging.

 

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About the Author
Susan is a Product Marketing Manager for AIML at Intel. She has her Ph.D. in Human Factors and Ergonomics, having used analytics to quantify and compare mental models of how humans learn complex operations. Throughout her well-rounded career, she has held roles in user-centered design, product management, customer insights, consulting, and operational risk.