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Explore documentation for Anaconda’s tools, created to streamline your data science, machine learning, and AI workflows. Select a tool below to get started with installation, quick start guides, tutorials, and reference materials.
Want to get started quickly? Use Anaconda Navigator to manage environments and launch applications from a graphical interface, or try Anaconda Notebooks for instant cloud-based development.

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Tools

Anaconda Desktop

Desktop application with secure local model deployment, interactive chat and API server capabilities, and Anaconda Platform integration.*

Anaconda Navigator

Desktop application with package management, environment control, and development tools in one unified interface.

Anaconda Notebooks

Jupyter notebooks with collaboration features, a built-in AI assistant, and seamless sharing. Work in the cloud or use pre-configured environments locally.

Anaconda AI Navigator

Desktop application with a local AI model repository and built-in inference server capabilities. Download, manage, and serve open-source LLMs directly on your machine without cloud dependencies.

Anaconda.org

Package repository and distribution platform for hosting and discovering conda packages.

Anaconda Toolbox Excel Add-in

Analyze data, create visualizations, and build models with Python directly in Microsoft Excel.
* Anaconda Desktop is currently available through a limited early access program. Similar actions can be taken with Anaconda AI Navigator.

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Common workflows

  1. Create a new conda environment in Anaconda Navigator.
  2. Install your required packages.
  3. Activate your environment.
  4. Launch Jupyter Notebook or your preferred IDE.
  5. Start coding and analyzing your data.
  1. Create a project in Anaconda Toolbox for notebooks.
  2. Share the project with your team members.
  3. Sync the project to keep your work up-to-date.
  4. Publish your notebook with Panel to share it as an interactive web app.
  1. Browse available models in Anaconda AI Navigator.
  2. Download your chosen model to your local machine.
  3. Chat with the model to test its capabilities.
  4. Load the model into the built-in inference server and connect to the local API endpoint.
  1. Develop and test your package locally.
  2. Build and upload your package as a conda package to Anaconda.org.
  3. Manage your hosted package while it’s live on Anaconda.org.
  1. Install the Anaconda Toolbox Excel Add-in.
  2. Write Python code directly in Excel cells.
  3. Generate visualizations and insights without exporting data.
  4. Use Anaconda Assistant to help you generate ideas and debug issues.