Search Results for "notebook" - Page 3
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Showing 121 open source projects for "notebook"
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PySchool
Installable / Portable Python Distribution for Everyone.
PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4... -
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The BLT Toolkit is an extension to Tcl and Tk. It adds new commands and widgets to the Tcl interpreter. Included widgets are 2D graph, barchart, stripchart, tab notebook, and tree viewer.
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MindForger
Thinking notebook and Markdown editor
Are you drowning in information, but starving for knowledge? Where do you keep your private remarks like ideas, personal plans, gift tips, how-tos, dreams, business vision, finance strategy, auto coaching notes? Loads of documents, sketches and remarks spread around the file system, cloud, web and Post-it notes? Are you affraid of your knowledge privacy? Are you able to find then once you create them? Do you know how are they mutually related when you read or write them? No? MindForger is... -
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Jupyter Nbextensions Configurator
A jupyter notebook serverextension providing config interfaces
A server extension for jupyter notebook which provides configuration interfaces for notebook extensions (nbextensions). The jupyter_nbextensions_configurator jupyter server extension provides graphical user interfaces for configuring which nbextensions are enabled (load automatically for every notebook). In addition, for nbextensions which include an appropriate yaml descriptor file (see below), the interface also renders their markdown readme files, and provides controls to configure the nbextensions' options. -
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Django Notebook
Django + shell_plus + Jupyter notebooks made easy
Django + shell_plus + Jupyter notebooks made easy. A Jupyter notebook with access to objects from the Django ORM is a powerful tool to introspect data and run ad-hoc queries. Built-in integration with the imported objects from django-extensions shell_plus. Saves the state between sessions so you don't need to remember what you did. Inheritance diagrams on any object, including ORM models. -
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PyNotes
An advanced Emacs-like text editor and IDE made in Python.
PyNotes is an advanced Emacs-like text editor and IDE made in Python, but much simpler for new users. -
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ipytest
Pytest in IPython notebooks
ipytest allows you to run Pytest in Jupyter notebooks. ipytest aims to give access to the full pytest experience and to make it easy to transfer tests out of notebooks into separate test files. -
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sqlitebiter
A CLI tool to convert CSV / Excel / HTML / JSON / Jupyter Notebook
A CLI tool to convert CSV / Excel / HTML / JSON / Jupyter Notebook / LDJSON / LTSV / Markdown / SQLite / SSV / TSV / Google-Sheets to an SQLite database file. -
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databooks
A CLI tool to reduce the friction between data scientists
databooks is a package to ease the collaboration between data scientists using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and resolution of git conflicts when encountered. Simply specify the paths for notebook files to remove metadata. By doing so, we can already avoid many of the conflicts. Specify the paths for notebook files with conflicts to be fixed. Then, databooks finds the source notebooks that caused the conflicts and compares them (so no JSON manipulation!) Specify paths of notebooks to be checked, an expression or recipe of what you'd like to enforce. databooks will run your checks and raise errors if any notebook does not comply with the desired metadata values. ... -
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YCBlogs
A comprehensive collection of technical blog notes
...Large collections of technical questions make it useful for review and interview preparation. Most content is stored as Markdown, allowing the collection to function as a searchable long-term engineering notebook. -
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hloc
Visual localization made easy with hloc
...We provide step-by-step guides to localize with Aachen, InLoc, and to generate reference poses for your own data using SfM. Just download the datasets and you're reading to go! The notebook pipeline_InLoc.ipynb shows the steps for localizing with InLoc. It's much simpler since a 3D SfM model is not needed. We show in pipeline_SfM.ipynb how to run 3D reconstruction for an unordered set of images. This generates reference poses, and a nice sparse 3D model suitable for localization with the same pipeline as Aachen. -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning... -
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Alphafold
Open source code for AlphaFold
...Please also refer to the Supplementary Information for a detailed description of the method. You can use a slightly simplified version of AlphaFold with this Colab notebook or community-supported versions. The total download size for the full databases is around 415 GB and the total size when unzipped is 2.2 TB. Please make sure you have a large enough hard drive space, bandwidth and time to download. We recommend using an SSD for better genetic search performance. -
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vim-jukit
Jupyter-Notebook inspired Neovim/Vim Plugin
REPL plugin and Jupyter-Notebook alternative for (Neo)Vim. This plugin is aimed at users in search for a REPL plugin with lots of additional features. -
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CARTOframes
CARTO Python package for data scientists
A Python package for integrating CARTO maps, analysis, and data services into data science workflows. Python data analysis workflows often rely on the de facto standards pandas and Jupyter notebooks. Integrating CARTO into this workflow saves data scientists time and energy by not having to export datasets as files or retain multiple copies of the data. Instead, CARTOframes give the ability to communicate reproducible analysis while providing the ability to gain from CARTO's services like... -
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codi.vim
The interactive scratchpad for hackers
...It focuses on minimal setup so you can open a buffer, set a filetype, and start experimenting immediately. Because results update incrementally, it is useful for learning, debugging, or documenting small examples. It turns Vim into a lightweight computational notebook while keeping the modal editing experience intact. -
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Hydrogen
Run code interactively, inspect data, and plot
...By bringing the interactive style of Light Table to the rock-solid usability of Atom, Hydrogen makes it easy to write code the way you want to. You also may be interested in our latest project – 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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Jupyter Notebooks extensions
A collection of various notebook extensions for Jupyter
The jupyter_contrib_nbextensions package contains a collection of community-contributed unofficial extensions that add functionality to the Jupyter notebook. These extensions are mostly written in Javascript and will be loaded locally in your browser. For Jupyter version 4 or 5, use the master branch of the repository. Most nbextensions have been updated to work with both Jupyter 4.x and 5.x, but occasionally things get missed, or the Jupyter API changes in a minor version update, so if anything doesn't work as you'd expect/hope, please do check the issues, or open a new one as necessary! ... -
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starboard-notebook
In-browser literate notebooks
starboard-notebook is an in-browser literate notebook runtime that enables users to write, edit, and interact with computational documents directly in the browser without needing a traditional backend notebook server. The project is built around an innovative runtime that interprets code cells and markdown in a way that feels fluid and interactive, often bridging concepts from classical notebook tools with modern web technologies. -
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Amazon SageMaker Operators Kubernetes
Amazon SageMaker operator for Kubernetes
...With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. It also provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment. With native support for bring-your-own-algorithms and frameworks, SageMaker offers flexible distributed training options that adjust to your specific workflows. ... -
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CCG
CCG (Crud Class Generator) is a ORM tool for .Net
...*CCG is easy to use, because; it is developer-friendly *CCG is practical, because; it allows to make many crud processes without writing SQL query *CCG is fast because; The object size is very small and allowing multiple simultaneous operations to be performed by going to the database only once. Documentation: http://ccg.snazzydocs.com/ YouTube channel: https://www.youtube.com/@ccg_4dal AI Help: https://notebooklm.google.com/notebook/8fc8a1fa-6544-4f40-bf33-ee980899e28e/preview You can send your questions and suggestions to ccg4dal@gmail.com Do not hesitate to ask me any questions you may have. NOTE: To be able to use the generated classes in your project, you should download required files (CCGDataService, CCGHelper) as well. -
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RetroLab
JupyterLab distribution with a retro look and feel
RetroLab (also known as JupyterLab Retro, previously called JupyterLab Classic) is a JupyterLab distribution with a retro look and feel, more similar to the classic Jupyter notebook. -
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ipynb-quicklook
Generator for Jupyter/IPython notebooks without further dependencies
A Quick Look generator for Jupyter/IPython notebooks without further dependencies. This plugin has now been integrated into a native macOS app, Jupyter Notebook Viewer. This is the recommended way to install the QuickLook generator. A stand-alone Quick Look generator for Jupyter/IPython notebooks on macOS. Contents are rendered on-the-fly using nbviewer.js. -
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Jupyter Dash
Dash v2.11+ has Jupyter support built in
Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information. -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
...These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance.
