#jupyter — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #jupyter, aggregated by home.social.
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Check out @giswqs and his GeoLibre package. He's just released an R package here https://r.geolibre.app/
This is "free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data" is on my winter bucket list.
#geolibre #gis #gischat #geospatial #foss #opensource #maps #mapstodon
#jupyter -
I'm still trying to wrap my head around this, but it looks very interesting:
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If y'all would indulge me a late addition: the appropriate lines in the #RDKit code (https://github.com/rdkit/rdkit/blob/master/rdkit/Chem/Draw/__init__.py#L190-L224) can of course be modified to use the B&R blob I introduced in the essay.
What's hampering me from actually trying this out for myself is that due to RDKit not yet being supported by #Pyodide, a lot of the webservices that can run #Python from the browser (e.g. the online version of #jupyter) are also not able to load RDKit. (I have seen at least two proposals to use the JS version of RDKit instead, but I have not managed to make that work either.) Because I had written that essay, and am currently writing this toot from a smartphone (for a number of reasons, I don't have access to a computer I can use), indirectly using RDKit through Wolfram Cloud (basically the online version of Mathematica) is pretty much how I attempt to do cheminformatics experiments on a smartphone. :)
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Small update on the python-on-iOS front: the unnamed notebook app now has a name -- Pyodios -- and a new trick.
Swap between a local Pyodide kernel and a remote Jupyter backend mid-session. Want offline? Stay local. Want GPU? Call home. No drama either way.
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JupyterLite ist nun Teil des Projekts Jupyter
JupyterLite ist eine JupyterLab-Distribution, die vollständig im Webbrowser ausgeführt wird und ohne Backend auskommt. Die Kernel werden mithilfe von WebAssembly direkt im Browser gestartet, wodurch ein Anwendungsserver überflüssig wird. https://kantel.github.io/posts/2026021602_jupyter_lite/ #JupyterLite #Jupyter #JupyterLab #Python #PyScript #Pyodide #P5js #DataScience #StatischeSeiten
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I made a short tutorial on understanding #GradientDescent in #MachineLearning, including interactive #Jupyter notebooks to play around with:
🌍 https://www.fabriziomusacchio.com/blog/2023-03-27-gradient_descent/
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Chapter 21 of http://learnpythonwithjupyter.com is out! It is a big recap of lists, with more methods and tricks. I hope you will find it useful! #Python #computationalthinking #Jupyter
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I did not realize you can post up to 100GB of data to #Kaggle and they provide access to computational resources and #Jupyter notebooks.
We're thinking about automatically posting all our #PUDL data there, and maybe running community competitions to help solve entity matching, anomaly detection, and imputation problems. Is there any downside to doing this?
#OpenData #MachineLearning #DataScience #EnergyTransition #EnergyTwitter #EnergyMastodon
https://www.kaggle.com/datasets/zaneselvans/catalyst-cooperative-pudl
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Someone asked how to solve the Advent of Code puzzle of 2015 day 15 https://adventofcode.com/2015/day/15 so I made this Python Jupyter notebook which shows a possible approach that is not brute force. If they can generalise this to the actual problem with 4 instead of 2 variables then that will be a useful introduction to gradient descent. https://ee1.nl/code/aoc2015-15.html
#AdventOfCode #AoC2015 #LinearAlgebra #Optimization #GradientDescent #Python #Jupyter #programming #puzzle
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Yo, here is a new PUDL data release, including updates to all the data through the end of 2021. #FERC Form 1, #EIA 860/923, #EPA CEMS, etc. Tarball includes the #SQLite DBs + #ApacheParuqet for the CEMS, a #Docker container with the software environment used to create them, and some example #Jupyter notebooks!
#OpenData #EnergyMastodon #EnergyTwitter #Energy #PyData #ClimateChange #Policy #CatalystCoop #pudl #DataEngineering #DataScience
