Data Science workgroup: Difference between revisions

Line 2:

This workgroup is dedicated towards improving the state of the data science stack in Nixpkgs. This includes work on packages and modules for scientific computation, artificial intelligence and data processing, as well as data science IDEs.

There have been some great examples of great work done on the data science infra :

There have been some great examples of great work done on libraries:

* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+nlp+ nlp]

* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+sklearn scikit-learn]

* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+tensorflow tensorflow]

but notably also on the data science infra :

* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+jupyter Jupyter]

Line 39:

Line 45:

</nowiki>}}

~~and libraries:~~

* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+nlp+ nlp]

* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+sklearn scikit-learn]

* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+tensorflow tensorflow]

It looks like NixOS is well on its way to becoming a solid data science platform; the reproducible and language agnostic approach is a natural match to the task. But perhaps a coordinated effort be fruitful step up the game?

~~But could a coordinated effort be fruitful step up the game?~~ Lets continue the discussion here and at #nixos-data.

Lets continue the discussion here and at #nixos-data.

== Channels ==

@@ Line 2: / Line 2: @@
 This workgroup is dedicated towards improving the state of the data science stack in Nixpkgs. This includes work on packages and modules for scientific computation, artificial intelligence and data processing, as well as data science IDEs.
-There have been some great examples of great work done on the data science infra :
+There have been some great examples of great work done on libraries:
+* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+nlp+ nlp]
+* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+sklearn scikit-learn]
+* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+tensorflow tensorflow]
+ but notably also on the data science infra :
 * [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+jupyter Jupyter]
@@ Line 39: / Line 45: @@
 </nowiki>}}
-and libraries:
-* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+nlp+ nlp]
-* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+sklearn scikit-learn]
-* [https://github.com/NixOS/nixpkgs/pulls?utf8=%E2%9C%93&q=is%3Apr+tensorflow tensorflow]
+It looks like NixOS is well on its way to becoming a solid data science platform; the reproducible and language agnostic approach is a natural match to the task. But perhaps a coordinated effort be fruitful step up the game?
-But could a coordinated effort be fruitful step up the game? Lets continue the discussion here and at #nixos-data.
+Lets continue the discussion here and at #nixos-data.
 == Channels ==