Use GitHub Copilot in Jupyter notebooks for data analysis, visualization, machine learning, and pandas operations.
Guide to using GitHub Copilot for data science workflows in Jupyter notebooks. Covers pandas operations, matplotlib/seaborn visualization code generation, scikit-learn model building, data cleaning prompts, SQL query generation from natural language, notebook-specific slash commands, and tips for working with large datasets.
Learn how to use GitHub Copilot to convert issues into pull requests while managing premium request quotas. Covers model selection, step-by-step implementation, and community-tested workflow patterns.
Learn how to use GitHub Copilot for terminal command suggestions, including setup in Windows Terminal and VS Code, custom keybindings for commit messages, usage tracking with community tools, and creative CLI projects.
Learn how to build and use GitHub Copilot custom instructions to make the AI behave predictably in your repos. Covers setup, writing techniques, three generation methods, and real-world troubleshooting.
Learn how to set up and tune GitHub Copilot Code Review for automated PR feedback. Covers enabling the feature, writing custom instructions to reduce noise, and iterating on the setup for long-term value.
Learn how to set up GitHub Copilot in VS Code, JetBrains IDEs, and Neovim. This guide covers installation, authentication, inline suggestions, Copilot Chat, best practices, and advanced configuration with custom instructions for code review.
Master Copilot Agent Mode with practical examples for multi-file editing, terminal commands, and autonomous coding workflows.
Workflows from the Neura Market marketplace related to this CoPilot resource