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Video with transcript included: http://bit.ly/2l7vHfw
Jeff Smith covers some of the latest features from PyTorch - the TorchScript JIT compiler, distributed data parallel training, TensorBoard integration, new APIs, and more. He discusses some projects coming out of the PyTorch ecosystem like BoTorch, Ax, and PyTorch BigGraph. He digs into some of the use cases and industries where people are successfully taking PyTorch models to production.
This presentation was recorded at QCon New York 2019: http://bit.ly/2KFk7SO
The next QCon is Qcon San Francisco 2019 – Nov 11-13, 2019: http://bit.ly/2ZFJW9S
For more awesome presentations on innovator and early adopter topics check InfoQ’s selection of talks from conferences worldwide https://bit.ly/2tm9loz
#PyTorch #Facebook #ArtificialIntelligence
Earn money! Build recognition!
To learn more, contact editors@infoq.com with a link to your LinkedIn profile.
---------------------------------------------------------------------------------------------------------------------------------------
Video with transcript included: http://bit.ly/2l7vHfw
Jeff Smith covers some of the latest features from PyTorch - the TorchScript JIT compiler, distributed data parallel training, TensorBoard integration, new APIs, and more. He discusses some projects coming out of the PyTorch ecosystem like BoTorch, Ax, and PyTorch BigGraph. He digs into some of the use cases and industries where people are successfully taking PyTorch models to production.
This presentation was recorded at QCon New York 2019: http://bit.ly/2KFk7SO
The next QCon is Qcon San Francisco 2019 – Nov 11-13, 2019: http://bit.ly/2ZFJW9S
For more awesome presentations on innovator and early adopter topics check InfoQ’s selection of talks from conferences worldwide https://bit.ly/2tm9loz
#PyTorch #Facebook #ArtificialIntelligence
From Research to Production with PyTorch scalar quantity | |
38 Likes | 38 Dislikes |
1,108 views views | 157K followers |
Science & Technology | Upload TimePublished on 25 Sep 2019 |
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