~/conference

PyTorch Summer Hackathon at Menlo Park 2019

deep learning engineers, research scientists, applied machine learning researchers, computer vision engineers, speech and audio researchers, ml infrastructure engineers

PyTorch 1.2 features; PyTorch Hub model zoo; pretrained image models; transfer learning final-layer fine-tuning; torchtext supervised datasets; tokenizer and Transformer modules; torchaudio Kaldi compatibility; torchaudio resample and inverse STFT; torchvision video support; video dataset DataLoader integration; deployment with AWS and Flask

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Tips and Tricks on Hacking with PyTorch: A Quick TutorialBrad Heintz05m
Less than two days means pick ready-made assets: use open datasets from torch vision torch text and torch audio (many download and cache with a single line)…
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PyTorch 1.2 and PyTorch Hub: A Quick IntroductionSoumith Chintala, Ailing Zhang06m
PyTorch 1.2 released and PyTorch Hub (Beta) provide concrete, usable pieces: a hub with 25+ models across image, language, audio and GANs, ready-to-load via…
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Torchtext 0.4 with Supervised Learning Datasets: A Quick IntroductionGeorge Zhang06m
Torchtext 0.4 ships supervised datasets with one-command data loading, ready-made splits and an N‑gram option so text classification experiments run from a…
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Torchaudio 0.3 with Kaldi Compatibility, New Transforms: A Quick IntroductionJason Lian05m
Torchaudio 0.3 claims concrete additions: Kaldi compatibility by matching Kaldi binary parameters, a new resample transform, and inverse STFT implemented in…
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Torchvision 0.4 with Support for Video: A Quick IntroductionFrancisco Massa09m
torchvision 0.4 adds first‑class video support: efficient IO primitives that read/write video (and audio) on the fly so no pre‑conversion is needed, standard…
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