[FRIAM] Deep learning training material

[Russ Abbott]

Hi Pieter,

A few comments.

   - Much of the actual deep learning material looks like it came from the
   Kaggle "Deep Learning
   <https://www.kaggle.com/learn/intro-to-deep-learning>" sequence.
   - In my opinion, R is an ugly and *ad hoc* language. I'd stick to Python.
   - More importantly, I would put the How-to-use-Python stuff into a
   preliminary class. Assume your audience knows how to use Python and focus
   on Deep Learning. Given that, there is only a minimal amount of information
   about Deep Learning in the write-up. If I were to attend the workshop and
   thought I would be learning about Deep Learning, I would be
   disappointed--at least with what's covered in the write-up.

   I say this because I've been looking for a good intro to Deep Learning.
   Even though I taught Computer Science for many years, and am now retired, I
   avoided Deep Learning because it was so non-symbolic. My focus has always
   been on symbolic computing. But Deep Learning has produced so many
   extraordinarily impressive results, I decided I should learn more about it.
   I haven't found any really good material. If you are interested, I'd be
   more than happy to work with you on developing some introductory Deep
   Learning material.

-- Russ Abbott
Professor Emeritus, Computer Science
California State University, Los Angeles


On Thu, Jan 5, 2023 at 11:31 AM Pieter Steenekamp <
pieters at randcontrols.co.za> wrote:

> Thanks to the kind support of OpenAI's chatGPT, I am in the process of
> gathering materials for a comprehensive and hands-on deep learning
> workshop. Although it is still a work in progress, I welcome any interested
> parties to take a look and provide their valuable input. Thank you!
>
> You can get it from:
>
> https://www.dropbox.com/s/eyx4iumb0439wlx/deep%20learning%20training%20rev%2005012023.zip?dl=0
>
>
> Pieter
>
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