The repo is missing a LICENSE file, and the links to the data should also specify their redistribution policy / license. Why is this not standard practice when creating a repo these days?

I did not expect such a response to my post. Thank you for making the issue, and I updated it with a MIT licence.

In my defense, this is a repo I cobbled together on the side for my AI group. I did not expect it to get a lot of attention outside the group. Also, the code I've provided is more for educational purposes. I didn't really see people using the code in other open source projects. In respect to the data, I provided links to the public sources.

Because this is not a requirement : https://choosealicense.com/no-license/

Sure, it simplifies things for those who want to have a closer look.

No licence means that you can't even use the software. This seems very restrictive for a GitHub project

Have a look at the article I linked, the case of places such as GitHub is explained (TL;DR: the licence is derived from the TOS)

The article says you can view and fork the code, but it doesn't mean you can use it. It's very restrictive.

> Although a code host such as GitHub may allow you to view and fork the code, this does not imply that you are permitted to use, modify, or share the software for any purpose.

I stand corrected. Thanks for reading the TOS in detail.

Indeed, GitHub let's you fork but then you cannot do anything else. My understanding now is that forking makes no sense when there is no license.

it's been updated w/ MIT

The topics covered are fairly broad and overall it seems like a nice collection of notebooks for teaching. Also, I agree with the choice to use Anaconda to install the dependencies. In my experience teaching similar type workshops (to engineering undergrad and grad students), Anaconda provides a good balance of simplicity and coverage, particularly with audiences of varying backgrounds.

Thank you. I have been writing many notebooks in my AI journey. I included some of them with this workshop. Can't agree more about Anaconda!

A really interesting collection for teaching Data Science. But the "WorkshopScipy" and the "scientific computation" make reference to something like scipy.org. It seems that this repo has different interests.

The workshop was focused on using tools in the scipy.org ecosystem. If you take a peak at the slides and code, you'll see that I primarily stick to scipy stuff.

I recommend starting with Poke Pandas. And yes, I'm very proud of the name.