#scikit — Public Fediverse posts

Ich probiere gerade #scikit-rf mit #Python. Ich möchte Teile einer #LISN für eine #EMV Messung untersuchen.

(https://github.com/bvernoux/EMC_5uH_LISN/blob/master/5uH_LISN_V1_R0_schematic.pdf)

#EMC #Simulation #RF #HF #scikitrf

Ich probiere gerade #scikit-rf mit #Python. Ich möchte Teile einer #LISN für eine #EMV Messung untersuchen.

(https://github.com/bvernoux/EMC_5uH_LISN/blob/master/5uH_LISN_V1_R0_schematic.pdf)

#EMC #Simulation #RF #HF #scikitrf

In this article, we aim to explore and compare three of the most popular machine learning libraries: TensorFlow, PyTorch, and scikit-learn. Each of these tools has[..]

#machinelearning #ai #tensor #python #scikit

https://www.ml-nn.eu/a1/66.html

In this article, we aim to explore and compare three of the most popular machine learning libraries: TensorFlow, PyTorch, and scikit-learn. Each of these tools has[..]

#machinelearning #ai #tensor #python #scikit

https://www.ml-nn.eu/a1/66.html

Today’s learning 🗒️

Instead of spending an hour building a SAS Viya Decision Tree manually, I:

→ Built it with Python scikit-learn
→ Answered workbook questions before opening SAS
→ Verified, screenshot, export PDF
→ A full SASPy automation pipeline

#datascience #scikit

A sci-kit image experiment #skimage #scikit Code at: https://github.com/villares/sketch-a-day/tree/main/2024/sketch_2024_12_06
More sketch-a-day: https://abav.lugaralgum.com/sketch-a-day
I really need your support to keep going, if you can, donate any amount at: https://www.paypal.com/donate/?hosted_button_id=5B4MZ78C9J724 #Processing #Python #py5 #CreativeCoding

A sci-kit image experiment #skimage #scikit Code at: https://github.com/villares/sketch-a-day/tree/main/2024/sketch_2024_12_06
More sketch-a-day: https://abav.lugaralgum.com/sketch-a-day
I really need your support to keep going, if you can, donate any amount at: https://www.paypal.com/donate/?hosted_button_id=5B4MZ78C9J724 #Processing #Python #py5 #CreativeCoding

📝🐍 Шпаргалка з #Python з акцентом на #DataScience

Зокрема, наводяться приклади використання #JupyterNotebook, #NumPy, #SciPy, #Pandas, #Scikit, #Matplotlib, #Seaborn, #Bokeh.

The Python community is huge and diverse, in some aspects. I always like to point how professional software development is just a fraction of the huge number of ways that software is created. I remember seeing threads here o Mastodon of #Python developers who didn't understand why people used #conda (from Anaconda inc.) package management... Well, it is 2024 and there are parts of #scikit, scikit-geometry, you can't install with #pip :(( ... I wish I could have it on pip, to be honest, but large parts of the scientific community will use conda, and that's it.

The Python community is huge and diverse, in some aspects. I always like to point how professional software development is just a fraction of the huge number of ways that software is created. I remember seeing threads here o Mastodon of #Python developers who didn't understand why people used #conda (from Anaconda inc.) package management... Well, it is 2024 and there are parts of #scikit, scikit-geometry, you can't install with #pip :(( ... I wish I could have it on pip, to be honest, but large parts of the scientific community will use conda, and that's it.

Wydarzył się cud! Udało mi się doprowadzić testy #SciKit Image do działania bez Internetu w #Gentoo!

Na marginesie:

1. Autorzy włączają większość niezbędnych danych w archiwum sdist. Tyle że ich nie używają, i zamiast tego ściągają je drugi raz, prosto z repozytorium na GitHubie. Wzdych. (Jeżeli czyta to któryś z autorów, proszę o udawanie, żeście tego nie widzieili i nie usuwanie tych plików z archiwum sdist. Dzięki.)
2. Na dodatek, pobierają dodatkowe dane dla testów z dodatkowego repozytorium na GitLabie, i przenoszą i zmieniają nazwy plików.
3. Tak, dobrze widzicie. Kod jest na GitHubie, dane dla testów na GitLab.com (nie własnej instancji).

https://gitweb.gentoo.org/repo/gentoo.git/commit/?id=0110ec020dbdb46c859e584609ab056fcafa10c6

#Python

It's a miracle! I've managed to make #SciKit Image tests work offline in #Gentoo!

That said:

1. Upstream includes most of the test data in sdist. Except they don't use it, and instead fetch it all from the GitHub repository. Sigh. (If you're upstream, please pretend you didn't see this and do not remove the data from sdist. Thanks.)
2. On top of that, they fetch more test data from an additional GitLab repository, and move and rename it around.
3. Yes, you've read right. They keep code on GitHub, but test data on GitLab.com (not self-hosted).

https://gitweb.gentoo.org/repo/gentoo.git/commit/?id=0110ec020dbdb46c859e584609ab056fcafa10c6

#Python

It's a miracle! I've managed to make #SciKit Image tests work offline in #Gentoo!

That said:

1. Upstream includes most of the test data in sdist. Except they don't use it, and instead fetch it all from the GitHub repository. Sigh. (If you're upstream, please pretend you didn't see this and do not remove the data from sdist. Thanks.)
2. On top of that, they fetch more test data from an additional GitLab repository, and move and rename it around.
3. Yes, you've read right. They keep code on GitHub, but test data on GitLab.com (not self-hosted).

https://gitweb.gentoo.org/repo/gentoo.git/commit/?id=0110ec020dbdb46c859e584609ab056fcafa10c6

#Python

and, if needed, modify it.

there are many python libraries out there:

#OpenCV
#SciPy
#imageio
#scikit-image (skimage)
#matplotlib
#Wand
#Pillow (PIL Fork)

#SciKit-Build skopiowało zepsutą logikę nazywania katalogu budowy z #setuptools. Tak więc używa katalogu "3.10" zarówno dla CPythona 3.10, jak i dla #PyPy 3.10. Podczas gdy w setuptools ma to pomniejsze konsekwencje i można to łatwo obejść (zmieniając katalog budowy), ze SciKit-Build nie ma tak łatwo. Budowa dla CPythona 3.10 używa cache'a z PyPy 3.10 i instaluje moduły z PyPy 3.10. Tak, serio, kompletnie niewłaściwe, bezużyteczne pliki.

A najlepsze w tym wszystkim? Autorzy o tym doskonale wiedzą, i mają to w dupie: "Nie sądzę, że powinniśmy zrobić to lepiej niż setuptools" (tłum. własne). No super, po prostu zajebiście. Tyle że w setuptools można trywalnie zmienić katalog budowania, a SciKit-Build wymusza "_skbuild".

https://github.com/scikit-build/scikit-build/issues/633#issuecomment-1021846731

#Gentoo #Python #PEP517

#SciKit-Build copied the broken build directory naming logic from #setuptools. As a result, it uses a "3.10" directory both for CPython 3.10 and for #PyPy 3.10. Whereas with setuptools this has minor consequences and can be trivially worked around (via overriding build directories), this isn't the case for SciKit-Build. Here it means that the subsequent build for CPython 3.10 reuses the cache from PyPy 3.10 and installs PyPy 3.10 modules. Yes, seriously, completely wrong, useless files.

The best part? They know about it, and they just don't care: "I don't think we should do better than setuptools". Sure, great. Except that we can trivially globally override build directory in setuptools, and SciKit-Build just forces "_skbuild" on us.

https://github.com/scikit-build/scikit-build/issues/633#issuecomment-1021846731

#Gentoo #Python #PEP517

#SciKit-Build copied the broken build directory naming logic from #setuptools. As a result, it uses a "3.10" directory both for CPython 3.10 and for #PyPy 3.10. Whereas with setuptools this has minor consequences and can be trivially worked around (via overriding build directories), this isn't the case for SciKit-Build. Here it means that the subsequent build for CPython 3.10 reuses the cache from PyPy 3.10 and installs PyPy 3.10 modules. Yes, seriously, completely wrong, useless files.

The best part? They know about it, and they just don't care: "I don't think we should do better than setuptools". Sure, great. Except that we can trivially globally override build directory in setuptools, and SciKit-Build just forces "_skbuild" on us.

https://github.com/scikit-build/scikit-build/issues/633#issuecomment-1021846731

#Gentoo #Python #PEP517

Can you name that algorithm based on this dataflow representation?

It's Linear Discriminant Analysis as implemented by Scikit Learn!

I finished up a notebook showing how you can build an Array API compatible library with the egglog e-graph library in Python and use that to optimize a #scikit-learn algorithm with #numba

https://egg-smol-python.readthedocs.io/en/stable/tutorials/sklearn.html

For more context, I gave a talk on the broader goals this summer:

https://egg-smol-python.readthedocs.io/en/stable/explanation/2023_07_presentation.html

https://www.youtube.com/watch?v=Pbi2uV9vWPg

#pydata #egraph #python

⏱️ Say goodbye to hours spent troubleshooting.

🎯 It integrates with popular Python ML frameworks such as #PyTorch, #TensorFlow, #HuggingFace, #Scikit-Learn, #XGBoost, and #LangChain.

[3/4]

⏱️ Say goodbye to hours spent troubleshooting.

🎯 It integrates with popular Python ML frameworks such as #PyTorch, #TensorFlow, #HuggingFace, #Scikit-Learn, #XGBoost, and #LangChain.

[3/4]

Inne wiadomości ze świata #Python: nowy backend #pep517 #scikit-build-core okazuje się psuć #setuptools na jeszcze jeden sposób. Tym razem błąd zauważono przy wykorzystaniu #pdm-backend.

A, fail2ban też psuje. Może to ten sam problem.

scikit-build-core: https://github.com/scikit-build/scikit-build-core/issues/426
fail2ban: https://bugs.gentoo.org/909535
poprzedni bug (psuł rozszerzenia #RustLang): https://github.com/scikit-build/scikit-build-core/issues/413

In other #Python news, the new #scikit-build-core #pep517 backend turns out to break building extensions via #setuptools in yet another way, this time noticed via #pdm-backend.

Oh, and there's also this bug where it breaks fail2ban too. Perhaps it's the same issue.

scikit-build-core: https://github.com/scikit-build/scikit-build-core/issues/426
fail2ban: https://bugs.gentoo.org/909535
previous bug (breaking #RustLang extensions): https://github.com/scikit-build/scikit-build-core/issues/413

In other #Python news, the new #scikit-build-core #pep517 backend turns out to break building extensions via #setuptools in yet another way, this time noticed via #pdm-backend.

Oh, and there's also this bug where it breaks fail2ban too. Perhaps it's the same issue.

scikit-build-core: https://github.com/scikit-build/scikit-build-core/issues/426
fail2ban: https://bugs.gentoo.org/909535
previous bug (breaking #RustLang extensions): https://github.com/scikit-build/scikit-build-core/issues/413

There's a whole crowd of people out there who need to learn how to do the sklearn.

It's my AI & Machine Learning class.

#python #sklearn #scikit #ai #MachineLearning #BillieEilish

There's a whole crowd of people out there who need to learn how to do the sklearn.

It's my AI & Machine Learning class.

#python #sklearn #scikit #ai #MachineLearning #BillieEilish

Un buen #CheatSheet sobre la librería #Pandas de #Python.

:pdf: Descarga el PDF: https://www.webpages.uidaho.edu/~stevel/cheatsheets/Pandas%20DataFrame%20Notes_12pages.pdf

👨‍🎓 Autor: Mark Graph: https://nitter.it/Mark_Graph

🔗 Web de Pandas: https://pandas.pydata.org/

Otros CheatSheet de Pandas:

:pdf: Python for DataScience: https://www.utc.fr/~jlaforet/Suppl/python-cheatsheets.pdf

:pdf: Data Wrangling (Pandas): https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf

🔗 The Pandas dataframe: https://www.shanelynn.ie/using-pandas-dataframe-creating-editing-viewing-data-in-python/

#Library #Librería #Programación #Divulgación #Formación #DataScience #MatPlotLib #SciKit #SciPy #Numpy #openscience #OpenAccess

https://red.niboe.info/@jmrplens/109365168666029054

Un buen #CheatSheet sobre la librería #Pandas de #Python.

:pdf: Descarga el PDF: https://www.webpages.uidaho.edu/~stevel/cheatsheets/Pandas%20DataFrame%20Notes_12pages.pdf

👨‍🎓 Autor: Mark Graph: https://nitter.it/Mark_Graph

🔗 Web de Pandas: https://pandas.pydata.org/

Otros CheatSheet de Pandas:

:pdf: Python for DataScience: https://www.utc.fr/~jlaforet/Suppl/python-cheatsheets.pdf

:pdf: Data Wrangling (Pandas): https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf

🔗 The Pandas dataframe: https://www.shanelynn.ie/using-pandas-dataframe-creating-editing-viewing-data-in-python/

#Library #Librería #Programación #Divulgación #Formación #DataScience #MatPlotLib #SciKit #SciPy #Numpy #openscience #OpenAccess

https://red.niboe.info/@jmrplens/109365168666029054

'HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn', by Fábio M. Miranda, Niklas Köhnecke, Bernhard Y. Renard.

http://jmlr.org/papers/v24/21-1518.html

#hiclass #hierarchical #scikit

'HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn', by Fábio M. Miranda, Niklas Köhnecke, Bernhard Y. Renard.

http://jmlr.org/papers/v24/21-1518.html

#hiclass #hierarchical #scikit

you know, when you try to run a command on a #docker #container using `docker-compose run` and it fails due to a missing dependency (#scikit-learn) but then works when run from the terminal container? 🤔

https://stackoverflow.com/questions/75062390/why-does-running-manage-py-dumpdata-core-setting-setting-json-work-from-th

#WhyDidIDecideToWorkInIT #question

you know, when you try to run a command on a #docker #container using `docker-compose run` and it fails due to a missing dependency (#scikit-learn) but then works when run from the terminal container? 🤔

https://stackoverflow.com/questions/75062390/why-does-running-manage-py-dumpdata-core-setting-setting-json-work-from-th

#WhyDidIDecideToWorkInIT #question

My next few days will be trying to figure out how to use #NLTK and #scikit to make sense of average 3-4GB semi garbage data once a day „as real-time as possible“. Let’s see how this goes :) (I know how to use there tools, but the data is so bad even basic grouping is hard) #python

My next few days will be trying to figure out how to use #NLTK and #scikit to make sense of average 3-4GB semi garbage data once a day „as real-time as possible“. Let’s see how this goes :) (I know how to use there tools, but the data is so bad even basic grouping is hard) #python

New year offer on Machine Learning with PyTorch and Scikit-Learn book

You can buy it for just $5 (It is 90% of the offer)

https://www.packtpub.com/product/machine-learning-with-pytorch-and-scikit-learn/9781801819312

#MachineLearning #pytorch #scikit #python #ArtificialIntelligence #deeplearning

New year offer on Machine Learning with PyTorch and Scikit-Learn book

You can buy it for just $5 (It is 90% of the offer)

https://www.packtpub.com/product/machine-learning-with-pytorch-and-scikit-learn/9781801819312

#MachineLearning #pytorch #scikit #python #ArtificialIntelligence #deeplearning

Am I missing something? I am currently trying to compute a Kernel Density Estimator in sky coordinates for some asteroids ... using scikit learn.

Apparently, the Haversine metric expects the latitude as at the first input parameter.

Pro tip: read the documentation. I feel completely dumb after "de-bugging" my code for an hour. #scikit #datascience #machinelearning #Python

https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.haversine_distances.html#sklearn.metrics.pairwise.haversine_distances

Am I missing something? I am currently trying to compute a Kernel Density Estimator in sky coordinates for some asteroids ... using scikit learn.

Apparently, the Haversine metric expects the latitude as at the first input parameter.

Pro tip: read the documentation. I feel completely dumb after "de-bugging" my code for an hour. #scikit #datascience #machinelearning #Python

https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.haversine_distances.html#sklearn.metrics.pairwise.haversine_distances

Let's be pragmatic about #OpenScience

If you want to be fully open you need to #OpenSource your code and to maintain it!
Giving requirements or even a #docker image is not enough. Code rots!
(If you want to write tests its even better 😍)

Let's take #scikit-learn as an example. Using Pydeps we can create a map of internal and external dependencies of it. And it's without counting on other dependencies you might have…

#ML #AI #Science #Programming

Let's be pragmatic about #OpenScience

If you want to be fully open you need to #OpenSource your code and to maintain it!
Giving requirements or even a #docker image is not enough. Code rots!
(If you want to write tests its even better 😍)

Let's take #scikit-learn as an example. Using Pydeps we can create a map of internal and external dependencies of it. And it's without counting on other dependencies you might have…

#ML #AI #Science #Programming

One of my favorite #scikit-hep #python packages is #vector https://github.com/scikit-hep/vector by @henryiii et.al. Provides #numpy / awkward-arrays of 3 & 4-vectors with broadcasted vector methods, including relativistic operations such as #lorentz boosting, as one might now from #ROOT vectors. Such a nice abstraction, writing vector math is as easy as doing it by hand and also runs super fast. Using this package almost feels like cheating. 1/N

Un buen #CheatSheet sobre la librería #Pandas de #Python.

📄 Descarga el PDF

👨‍🎓 Autor: Mark Graph

🔗 Web de Pandas

Otros CheatSheet de Pandas:

• 📄Python for DataScience

• 📄Data Wrangling (Pandas)

• 🔗The Pandas dataframe

#Library #Librería #Programación #Divulgación #Formación #DataScience #MatPlotLib #SciKit #SciPy #Numpy
@academicsunite @academicchatter @phdlife @phdstudents