interactive computing notebook environment
For un entorno interactivo para ciencia de datos, the strongest matches are jupyterlab/jupyterlab (JupyterLab is the next-generation web-based interface for Project Jupyter), udlbook/udlbook (This repository contains deep learning educational notebooks that run) and jupyter/jupyter (Jupyter is the core Jupyter project that provides the). jupyter/notebook is also worth a look. Each is ranked by relevance to your query, popularity and recent activity.
Curamos repositorios de código abierto en GitHub que coinciden con “jupyter”. Los resultados están clasificados por relevancia según tu búsqueda; usa los filtros de abajo para acotar o refina con IA.
Resultados para “un entorno interactivo para ciencia de datos”
Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
- jupyterlab/jupyterlab
jupyterlab/jupyterlab
15,210Ver en GitHubJupyterLab is a web-based development environment designed for interactive data science, collaborative research, and computational notebook authoring. It provides a unified workspace where users can execute code, manage computational kernels, and create documents that integrate live code, rich data visualizations, and narrative text. The platform is built on a modular architecture that supports extensive customization through a plugin system. This framework allows for the dynamic loading of extensions, enabling users to define custom file viewers, interface themes, and keyboard shortcuts. By
JupyterLab is the next-generation web-based interface for Project Jupyter, providing a full interactive computing environment with live code execution, multi-language kernel support, notebook documents, rich outputs, and extensive extensibility via plugins — exactly the flagship ecosystem the visitor is looking for.
TypeScriptInteractive Notebooks - udlbook/udlbook
udlbook/udlbook
9,099Ver en GitHubudlbook is a deep learning educational repository and a collection of interactive learning notebooks designed for studying neural network architectures. It serves as a digital repository of formatted mathematical equations and guided examples for learning deep learning concepts. The project provides a mathematical reference for supervised learning and neural network theory using LaTeX rendering. It includes interactive technical documentation and executable notebooks covering gradients, convolutions, and transformers. The system manages educational materials through a file-system based organ
This repository contains deep learning educational notebooks that run on a Jupyter environment, but it is a collection of learning content rather than the Jupyter Notebook or JupyterLab platform itself.
Jupyter NotebookLaTeX Math Rendering - jupyter/jupyter
jupyter/jupyter
15,327Ver en GitHubJupyter is an interactive computing platform and data science workspace designed for creating documents that combine live code, equations, visualizations, and narrative text. It provides a polyglot notebook interface that connects a frontend user interface to various backend language engines through a standardized kernel protocol for real-time code evaluation. The system enables polyglot programming workflows, allowing multiple different programming languages to run within a single interface. It supports computational document authoring and data science exploration by allowing users to execut
Jupyter is the core Jupyter project that provides the interactive notebook and JupyterLab interface, supporting live code in multiple languages via kernels, rich outputs, and extensibility—directly matching the flagship ecosystem described.
PythonInteractive Computing EnvironmentsData Science WorkspacesExploratory Data Analysis Workflows - jupyter/notebook
jupyter/notebook
13,204Ver en GitHubThis project is a browser-based interactive computing environment and data science IDE. It serves as a literate programming tool that allows users to create documents combining live code, mathematical equations, visualizations, and narrative text. As a polyglot notebook interface, it connects to various language kernels to execute code and render output within a single interface. The application distinguishes itself by separating the frontend interface from a remote compute engine through a language-agnostic kernel interface. This allows it to support multiple programming languages while main
This is the official Jupyter Notebook, the original browser-based interactive computing environment that combines live code, rich outputs, and narrative text with multi-language kernel support, exactly matching the flagship ecosystem requested.
Jupyter NotebookExecution KernelsInteractive Data Science EnvironmentsBlock-Based Document Models
