Search Results for "jupyter desktop"
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Showing 10 open source projects for "jupyter desktop"
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JupyterLab Desktop
JupyterLab desktop application, based on Electron
JupyterLab Desktop is the cross-platform desktop application for JupyterLab. It is the quickest and easiest way to get started with Jupyter notebooks on your personal computer, with the flexibility for advanced use cases. JupyterLab Desktop can be launched from the GUI of your operating system by clicking the application's icon or by using jlab command from the command line. Double-clicking .ipynb files is also supported and it will launch JupyterLab Desktop and load the notebook file. -
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JupyterLab
JupyterLab computational environment
JupyterLab is the next-generation web-based user interface for Project Jupyter. Try it on Binder. JupyterLab follows the Jupyter Community Guides. JupyterLab enables you to work with documents and activities such as Jupyter notebooks, text editors, terminals, and custom components in a flexible, integrated, and extensible manner. You can arrange multiple documents and activities side by side in the work area using tabs and splitters. Documents and activities integrate with each other, enabling... -
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Hydrogen
Run code interactively, inspect data, and plot
... – interact – a desktop application that wraps up the best of the web-based Jupyter notebook. Watch expressions let you keep track of variables and re-run snippets after every change. Completions from the running kernel, just like autocomplete in the Chrome dev tools. Code can be inspected to show useful information provided by the running kernel. One kernel per language (so you can run snippets from several files, all in the same namespace). -
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tqdm
A Fast, Extensible Progress Bar for Python and CLI
... overhead and uses smart algorithms to predict the remaining time and skip unnecessary iteration displays. It works on just about any platform, console or in a GUI, as well as IPython/Jupyter notebooks. -
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gophernotes
The Go kernel for Jupyter notebooks and nteract
gophernotes is a Go kernel for Jupyter notebooks and nteract. It lets you use Go interactively in a browser-based notebook or desktop app. Use gophernotes to create and share documents that contain live Go code, equations, visualizations and explanatory text. These notebooks, with the live Go code, can then be shared with others via email, Dropbox, GitHub and the Jupyter Notebook Viewer. Go forth and do data science, or anything else interesting, with Go notebooks! This project utilizes a Go... -
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moebinv
C++ libraries for manipulations in non-Euclidean geometry
These are two C++ libraries for symbolic, numeric and graphical manipulations in non-Euclidean geometry. There is GUI which allows to interact with these libraries by mouse clicks. On a dipper level the first library Cycle implements basic operations on cycles (quadrics) through FSCc construction. The second library Figure operates on ensembles of cycles connected by Moebius-invariant relations, e.g. orthogonality. Both libraries are based on the Clifford algebra capacities of the... -
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ML workspace
All-in-one web-based IDE specialized for machine learning
All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly... -
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nteract
The interactive computing suite for you
... notebooks in a desktop app or in your favorite editor, nteract provides you the tools you need to leverage the full power of interactive notebooks and the Jupyter ecosystem. Interactive notebooks and REPLs are a powerful way for people to interact with machines. nteract provides a client-side SDK for integrating notebook and REPL UIs into your software. The same SDK used to build the nteract suite of applications is available to you. -
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Neurolinux
Neurolinux, the Deep Learning OS
Neurolinux, the Deep Learning OS, with all necessary tools and libraries pre-installed. Pytorch, Tensorflow Jupyter notebooks...etc -
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Python4Proteomics Course
Python course for Proteomics analysis
Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md
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