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papermill - 📚 Parameterize, execute, and analyze notebooks

  •    Python

Papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks. To parameterize your notebook designate a cell with the tag parameters.

awesome-google-colab - Google Colaboratory Notebooks and Repositories (by @firmai)

  •    Jupyter

A curated list of repositories with fully functional click-and-run colab notebooks with data, code and description. The code in these repositories are in Python unless otherwise stated. To learn more about they whys and hows of Colab see this post. For a few tips and tricks see this post.

orchest - Build data pipelines, the easy way 🛠️

  •    Python

No frameworks. No YAML. Just write Python and R code in Notebooks. 💡 Watch the full narrated video to learn more about building data pipelines in Orchest.

Bokeh - Interactive Data Visualization in the browser, from Python

  •    Python

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.

amazon-sagemaker-examples - Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

  •    Jupyter

These examples provide a gentle introduction to machine learning concepts as they are applied in practical use cases across a variety of sectors.These examples provide quick walkthroughs to get you up and running with Amazon SageMaker's custom developed algorithms. Most of these algorithms can train on distributed hardware, scale incredibly well, and are faster and cheaper than popular alternatives.

mash_2016_sklearn_intro - Material for the MASH course on introduction to scikit-learn

  •    Jupyter

Instructors: Fabian Pedregosa and Fajwel Fogel. This repository contains notebooks and other files associated with the MASH course introduction to Scikit-learn.

cauldron - The Unnotebook: A Production-Ready Data Environment Built for DataOps Workflows

  •    Python

which must be executed in the root project directory of your local copy of Cauldron. Cauldron can be used as either through its Command Line Interface (CLI) or with the Cauldron desktop application. For more information about the desktop application visit http://www.unnotebook.com where you can find the download links and documentation. The rest of this README describes using Cauldron directly from the command line.

notebooks - IPython Notebooks

  •    Jupyter

Some Jupyter Notebooks on geophysics and seismic interpretation.

xlines - X lines of Python

  •    Jupyter

An Agile blog series exploring common geosciencey workflows in x lines, where ideally x ≤ 10 but not necessarily, I haven't thought it through properly yet. These will be Jupyter Notebooks running on Azure Notebooks. Click the launch azurenb button to start the interactive Azure Notebooks (thanks to Dino and Paige at Azure for helping with this, and to Jesper Dramsch for helping me keep it straight).

PPExtensions - Set of iPython and Jupyter extensions to improve user experience

  •    Python

PPExtensions is a suite of ipython and jupyter extensions built to improve user experience and reduce time to market in Jupyter notebooks.

examples - Example nteract notebooks with links to execution on mybinder.org

  •    Jupyter

Go ahead and give these notebooks a try. This repository has collections of nteract notebooks to try out on Binder. Click the link of an individual example or the language heading for a bundle of notebooks.

notebooks - :notebook: A growing collection of Jupyter Notebooks written in Python, OCaml and Julia for science examples, algorithms, visualizations etc

  •    Jupyter

This repository hosts some Jupyter Notebooks, covering various subjects. Go to nbviewer to read them. At the beginning, this repository was only here to host some small experiments, for me to learn how to use the wonderful Jupyter tools correctly (baby notebooks 🍼)...

vscode-dotnet-pack - .NET Extension Pack for VSCode. The best of C#, F#, and .NET Interactive.

  •    TypeScript

The .NET Extension Pack is the ultimate collection of extensions for working with .NET in VS Code. The C# extension is powered by OmniSharp.

machine-learning-scripts - Collection of scripts and tools related to machine learning

  •    Jupyter

This repository is a miscellaneous collection of scripts and tools related to machine learning. Currently consists of Jupyter notebooks in the notebooks subdirectory, and example SLURM scripts in slurm. Materials related to specific courses can be found in the courses subdirectory.

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