Visual Studio Code container development troubleshooting tips and tricks

Learn how to build machine learning applications in Azure Machine Learning using the Visual Studio Code extension

Visual Studio Code Remote Development Frequently Asked Questions (FAQ) for SSH, Containers, and WSL

Run a set of prompts with variables or function calls with an imported or synthetically generated dataset towards the selected models and parameters.

Use custom dataset to fine-tune a generative AI model in the Azure cloud or locally with GPUs. Deploy the fine-tuned model to the Azure cloud or download incremental files from fine-tuned model.

Connect over SSH with Visual Studio Code

Evaluate AI models, prompts, and agents using AI Toolkit's comprehensive evaluation system. Import datasets, run evaluations with built-in evaluators like F1 score, relevance, coherence, and similarity, or create custom LLM-based and code-based evaluators. Visualize and compare results in tables and charts.

Learn how to use Git version control basics in Visual Studio Code.

Visual Studio Code supports a Portable mode that enables moving your installation and related data to a different location.

Set up Copilot in VS Code