The Three Elements of PyTorch

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.

[geekyprogrammer]

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

[minhsangnguyen]

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

[aboubacardiallo]

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.

[sushantpenshanwar]

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

[muhammadbilalshahid]

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

[dmitrymalishev]

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.