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Machine Learning Useful Pack

Machine Learning Useful Pack

WYRX

|
232 installs
| (0) | Free
This extension pack is designed for Python development with Jupyter Notebook and GitHub Copilot, utilizing Ruff for formatting.
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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Machine Learning Useful Pack

Description

This extension pack is designed for Python development with Jupyter Notebook and GitHub Copilot, utilizing Ruff for formatting.

Extensions Included

  • charliermarsh.ruff: Provides linting and formatting for Python code to ensure code quality and consistency.
  • eamodio.gitlens: Enhances Git capabilities within VS Code, making it easier to understand code changes and history.
  • foxundermoon.shell-format: Formats shell scripts for better readability and maintenance.
  • github.copilot: Offers AI-powered code suggestions to speed up development.
  • github.copilot-chat: Enables interactive AI-driven coding assistance and troubleshooting.
  • mechatroner.rainbow-csv: Highlights CSV files for easier data manipulation and visualization.
  • ms-python.debugpy: Facilitates debugging of Python applications.
  • ms-python.isort: Automatically sorts Python imports to maintain a consistent order.
  • ms-python.python: Provides core Python support, including IntelliSense, linting, and debugging.
  • ms-python.vscode-pylance: Enhances Python language support with fast and feature-rich IntelliSense.
  • ms-toolsai.jupyter: Integrates Jupyter Notebooks into VS Code for interactive data analysis and visualization.
  • ms-toolsai.jupyter-keymap: Adds keybindings for Jupyter Notebooks to improve productivity.
  • ms-toolsai.jupyter-renderers: Enhances the rendering of Jupyter Notebook outputs.
  • ms-toolsai.vscode-jupyter-cell-tags: Allows tagging of Jupyter Notebook cells for better organization and navigation.
  • ms-toolsai.vscode-jupyter-powertoys: Adds additional functionalities to Jupyter Notebooks for advanced usage.
  • ms-toolsai.vscode-jupyter-slideshow: Enables the creation of presentations directly from Jupyter Notebooks.
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