[Learn-data-science] pyTorch Basics: Summary Meeting

[Eric Drechsler]

Hello aspiring pyTorch experts,

the discussion in our last meeting revealed that many of you would 
benefit from an overview of pyTorch basics first before diving into the 
deep end. We are currently running a doodle poll [1] to converge on a 
preferred meeting time.

We are still looking for volunteers to present a short, informal summary 
of selected modules in the basics course [2], which covers the following 
topics:

Module 1: Tensors, Derivatives, Dataset
Module 2: Linear Regression, Loss, Gradient Descent, Cost, Training
Module 3: Gradient Descent, Optimisation, Validation, early stop
Module 4: Linear Regression in depth: Prediction, multiple outputs

Digital glory and virtual cookies await! 🍪

For more information, visit our slack channel.
  - Your DS Group

[1] https://doodle.com/poll/z3a2whmr9gpt8bp6#calendar
[2] https://www.edx.org/course/pytorch-basics-for-machine-learning 
(choose the audit option for a free look at the course)

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