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PyTorch in Production, Research & Industry | Expert-Level AI Course
PyTorch Developer Conference 2019: Recap

PyTorch Developer Conference 2019: Recap

PyTorch in Production, Research & Industry | Expert-Level AI Course

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28 درس
11:11 PyTorch at Tesla - Andrej Karpathy, Tesla
10:08 Detectron2 - Next Gen Object Detection Library - Yuxin Wu
16:03 Privacy Preserving AI - Andrew Trask, OpenMined
06:31 Dataloader Design for PyTorch - Tongzhou Wang, MIT
52:07 PyTorch Developer Conference 2019 | Full Livestream
10:06 Research to Production: PyTorch JIT/TorchScript Updates - Michael Suo
09:54 Quantization - Dmytro Dzhulgakov
08:19 Model Interpretability with Captum - Narine Kokhilkyan
04:37 PyTorch ONNX Export Support - Lara Haidar, Microsoft
08:56 PyTorch Mobile - David Reiss
09:38 PyTorch in Robotics - Yisong Yue, Caltech
13:18 PyTorch at Uber - Sidney Zhang, Uber
06:52 Speech Extensions to Fairseq - Dmytro Okhonko
11:30 What’s new in PyTorch 1.3 - Lin Qiao
13:25 PyTorch Developer Conference Keynote - Mike Schroepfer
07:28 PyTorch at Microsoft - Saurabh Tiwary, Microsoft
23:10 PyTorch on Google Cloud TPUs - Google, Salesforce, Facebook
10:21 PyTorch at Dolby Labs - Vivek Kumar, Dolby Labs
10:45 StanfordNLP - Yuhao Zhang, Stanford
10:36 Collaborative Natural Language Inference - Sasha Rush, Cornell
36:55 PyTorch Developer Conference 2019 - Panel Discussion
03:44 Linear Algebra in PyTorch - Vishwak Srinivasan, CMU
05:23 Apex - Michael Carilli, NVIDIA
08:26 PyTorch Front-End Features: Named Tensors and Type Promotion - Gregory Chanan
10:36 CrypTen - Laurens van der Maaten
10:56 PyTorch Summer Hackathon Winners - Joe Spisak, Sebastien Arnold, Tristan Deleu
02:31 PyTorch Developer Conference 2019: Recap
10:45 Sotabench for Reproducible Research - Robert Stojnic, Papers with Code