The Three Elements of PyTorch

Ғылым және технология

Code: github.com/rasbt/machine-lear...
Slides: sebastianraschka.com/pdf/slid...
00:00 Three elements of PyTorch
02:10 (1) Tensor library
05:56 (2) Automatic differentiation engine
13:32 (3) Deep learning library
14:27 PyTorch in 3 Steps
15:17 Step 1: defining the model
23:32 Step 2: defining the training loop
30:20 Step 3: defining the dataset
39:34 Why do I like PyTorch?
42:25 Hands-on code demo
This talk is an hour long introduction to PyTorch focusing on its three core elements: tensor (array) computing, automatic differentiation, and deep learning utilities.

Пікірлер: 16

  • @muhammadbilalshahid8010
    @muhammadbilalshahid8010 Жыл бұрын

    This is such a useful video with just 2k views!!

  • @SebastianRaschka

    @SebastianRaschka

    Жыл бұрын

    Glad you liked it!

  • @geekyprogrammer4831
    @geekyprogrammer4831 Жыл бұрын

    Your lectures deserves a lot more views than it has. You are a brilliant professor!

  • @minhsangnguyen3465
    @minhsangnguyen3465 Жыл бұрын

    Such a great video! Definitely deserved more views! I like your way of explain things!

  • @SebastianRaschka

    @SebastianRaschka

    Жыл бұрын

    Thanks for the kind words, and I am glad to hear you liked it!

  • @aboubacardiallo8296
    @aboubacardiallo8296 Жыл бұрын

    Thank you for making these resources accessible for free and easy to understand, I am actually reading your Book (Machine Learning with PyTorch and Scikit-learn), all DL concepts are well explained with examples of codes thanks for that.

  • @SebastianRaschka

    @SebastianRaschka

    Жыл бұрын

    Glad to hear that both the videos and the book are useful to you!

  • @sushantpenshanwar
    @sushantpenshanwar Жыл бұрын

    This is super cool really !! Though I am aware about most of the concepts it was a treat watching it.

  • @dmitrymalishev6045
    @dmitrymalishev60452 жыл бұрын

    Thank you, this is a really good introduction to PyTorch which doesn't make you feel frightened of how many difficulties are inside =) If you look someday for a new topic to present, please consider making more elaborate comparison TensorFlow vs. PyTorch.

  • @SebastianRaschka

    @SebastianRaschka

    2 жыл бұрын

    Glad it was helpful! Haha, yeah, PyTorch vs TensorFlow is a very popular question/discussion topic. A side-by-side comparison with actual code might be helpful. I am just worried that by now by Tf are way too bad :P

  • @dmitrymalishev6045

    @dmitrymalishev6045

    2 жыл бұрын

    I expect it may turn out to be more intriguing! =) TF supports training with TPU, which several times faster than all GPUs. Also, TF seems to be faster in training and inference on CPU (while PyTorch most of the time better on GPU). Google with it's Kaggle, Colab, Cloud and HW is more powerful after all! And the most exciting combat - which one is better for production solutions, and here I lost the track, maybe you could give some insights.

  • @SebastianRaschka

    @SebastianRaschka

    2 жыл бұрын

    ​@@dmitrymalishev6045 Actually, if you use PyTorch Lightning or LightningLite on top of PyTorch, you get support for all of it :). GPU, TPU, IPU, HPU. And it's super easy!

  • @SebastianRaschka

    @SebastianRaschka

    2 жыл бұрын

    Here's a link if you are interested: pytorch-lightning.readthedocs.io/en/stable/starter/lightning_lite.html

  • @dmitrymalishev6045

    @dmitrymalishev6045

    2 жыл бұрын

    Thank you for the link! Looks like Lightning uses XLA to support TPU. Half a year ago PyTorch+XLA wasn't stable enough, some kernels just didn't work. Hope, it's better now, I'll give it a try on some upcoming Kaggle competition! =)

  • @AkashChandraGupta
    @AkashChandraGupta2 жыл бұрын

    Beauty

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