.NET Interactivetakes the power of .NET and embeds it into interactive experiences. One of these interactive experiences is notebooks. Notebooks are files that contain executable code, visualizations, and raw text all within the same file. Interactive notebooks are used extensively in data science and machine learning. They are great for data exploration and preparation, experimentation, model explainability, and education.
Since theannouncement of the Notebook Editorextension in Visual Studio last October, we've been constantly working to improve the experience. We've continuously made stability and performance improvements to the extension and in our most recent release we enabled keyboard shortcuts and deep-linking capabilities to automatically open notebooks in Visual Studio.
To go along with these updates and showcase the power of notebooks for data science and machine learning applications, we've put together aseries of notebooksthat cover getting started and end-to-end machine learning scenarios. This is the first version of these notebooks and we plan to continue iterating on them.
How can you get started?
On a recent episode ofVS Toolbox Live, we provided an overview of notebooks in Visual Studio and the machine learning notebook series. Take a look at that recording to get a sense of what notebooks are and how they can be useful for your workflows.
When you're ready to get started exploring the notebooks yourself: