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https://github.com/atcold/nyu-dlfl22

NYU Deep Learning Fall 2022
https://github.com/atcold/nyu-dlfl22

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NYU Deep Learning Fall 2022

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README

          

# NYU Deep Learning Fall 2022 (NYU-DLFL22)

Differential edition based on [NYU-DLSP21](https://github.com/Atcold/NYU-DLSP21/blob/master/README.md).

## New content

After the SP21 there have been three more editions (FL21, SP22, and FL22).
Some of the existing content has been updated and new lectures have been crafted.
So, I felt it was about time for releasing the goodies online.

Now, editing *all* the lectures while keeping my *current quality* is rather onerous.
Moreover, lectures that have not been changed substantially wouldn't bring much value *in addition to* those that have already been pushed online in the previous edition.
Therefore, this FL22 edition is going to be a *differential* one.
Meaning, it's going to be an ‘expansion’ based on the SP21 version.

You can choose to watch only the new videos (if you've already watched SP21) or you can watch video from the two editions, back to back.
Check out the table of contents on the [class website](https://atcold.github.io/NYU-DLFL22/) to create your own roadmap.

## Previous releases

Before NYU-DLFL22 there were…

- [NYU-DLSP21](https://github.com/Atcold/NYU-DLSP21/) (best video quality, full course)
- [NYU-DLSP20](https://github.com/Atcold/NYU-DLSP20) (major release, 16 translations)
- [NYU-DLSP19](https://github.com/Atcold/NYU-DLSP20/releases/tag/dlsp19)
- [AIMS-DLFL19](https://github.com/Atcold/NYU-DLSP20/releases/tag/aims-fl18)
- [CoDaS-HEP18](https://github.com/Atcold/NYU-DLSP20/releases/tag/v1.0.0)
- [NYU-DLSP18](https://docs.google.com/document/d/1_p1Mw-NtMGN_vpas_pchLsQC2u0NM5mTnRapBrQ2ivk/)
- [Purdue-DLFL16](https://docs.google.com/document/d/1ugJRMqQ_cCUQC1B8mSE0iro7sKrDT8-BnppTZv0rA08/)
- [torch-Video-Tutorials](https://github.com/Atcold/torch-Video-Tutorials)

## More info

Keep reading on the [class website](https://atcold.github.io/NYU-DLFL22/).