Building and Training Deep Learning Models in PyTorch

BCS Computational Tutorial Series with Valmiki Kothare, MIT.
In this tutorial, we will use deep learning on EEG and EMG mice data to predict sleep stages (Wakefulness, REM, Non-REM). We will walk through an example Jupyter Notebook in which we load a dataset, preprocess it, build a "residual-attention" network, train our model, and validate our performance on withheld data. In the process of going through the notebook, we will discuss briefly how to run this on OpenMind and how to parallelize training across multiple GPUs, as well as the reasoning behind the network architecture choice and the basic theory of the attention/transformer layer.
Google Colab Notebook - colab.research.google.com/dri...

[@AnimeshSharma1977]

No fluff, straight to point! Precisely what is needed to get going with remote multi server GPU deep-learning for translational medicine all within an hour!! Thanks for sharing 👍

[@john2875]

watched first 20 mins didn't understand anything . improve your teaching skills.
i mean your'e good and knowledgeable but try to teach like your'e teaching a kid okay.