Overview Brief: Purdue ECE 595 Computer Vision for Embedded Systems was a short (5 week, Fall 2022) online graduate course. Speaker: Suraj Subramanian, Developer Advocate, PyTorch Suraj is a developer advocate and ML engineer at Meta AI.

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Purdue ECE 595 Computer Vision for Embedded Systems was a short (5 week, Fall 2022) online graduate course. It's important to make efficient use of both server-side and on-device compute resources when developing ML applications. Speaker: Suraj Subramanian, Developer Advocate, PyTorch Suraj is a developer advocate and ML engineer at Meta AI.

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Speaker: Suraj Subramanian, Developer Advocate, PyTorch Suraj is a developer advocate and ML engineer at Meta AI. And, deep dive into PyTorch 1.0 with members of the core dev team including Soumith Chintala,

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  • Purdue ECE 595 Computer Vision for Embedded Systems was a short (5 week, Fall 2022) online graduate course.
  • And, deep dive into PyTorch 1.0 with members of the core dev team including Soumith Chintala,
  • It's important to make efficient use of both server-side and on-device compute resources when developing ML applications.
  • Speaker: Suraj Subramanian, Developer Advocate, PyTorch Suraj is a developer advocate and ML engineer at Meta AI.

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Check the Summary
Quantization - Dmytro Dzhulgakov

Quantization - Dmytro Dzhulgakov

It's important to make efficient use of both server-side and on-device compute resources when developing ML applications.

PyTorch: Bridging AI Research and Production // Dmytro Dzhulgakov // MLOps Coffee Sessions #63

PyTorch: Bridging AI Research and Production // Dmytro Dzhulgakov // MLOps Coffee Sessions #63

Read more details and related context about PyTorch: Bridging AI Research and Production // Dmytro Dzhulgakov // MLOps Coffee Sessions #63.

Hessian AWare Quantization V3: Dyadic Neural Network Quantization

Hessian AWare Quantization V3: Dyadic Neural Network Quantization

This is a brief description of HAWQV3, which is a Hessian AWare

Downsizing Neural Networks by Quantization - Introduction to Deep Learning

Downsizing Neural Networks by Quantization - Introduction to Deep Learning

Read more details and related context about Downsizing Neural Networks by Quantization - Introduction to Deep Learning.

Leaner, Greener and Faster Pytorch Inference with Quantization

Leaner, Greener and Faster Pytorch Inference with Quantization

Speaker: Suraj Subramanian, Developer Advocate, PyTorch Suraj is a developer advocate and ML engineer at Meta AI.

Lecture 7/A Quantization in PyTorch, , Computer Vision for Embedded Systems

Lecture 7/A Quantization in PyTorch, , Computer Vision for Embedded Systems

Purdue ECE 595 Computer Vision for Embedded Systems was a short (5 week, Fall 2022) online graduate course.

PyTorch Developer Conference 2018: Keynote & Deep Dive

PyTorch Developer Conference 2018: Keynote & Deep Dive

And, deep dive into PyTorch 1.0 with members of the core dev team including Soumith Chintala,

How to statically quantize a PyTorch model (Eager mode)

How to statically quantize a PyTorch model (Eager mode)

Read more details and related context about How to statically quantize a PyTorch model (Eager mode).

PyTorch Developer Conference 2019 | Full Livestream

PyTorch Developer Conference 2019 | Full Livestream

Read more details and related context about PyTorch Developer Conference 2019 | Full Livestream.

9.1 Quantization-aware training - code

9.1 Quantization-aware training - code

Read more details and related context about 9.1 Quantization-aware training - code.