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Iterative’s DVC Extension Turns VS Code Into ML Experimentation Platform


In this episode of TFiR Let’s Talk, Dmitry Petrov, Co-Founder and CEO of, sits down with Swapnil Bhartiya to discuss the recently released DVC Extension for Visual Studio Code. The open source project by Iterative aims to bring a full machine learning (ML) experimentation platform to Visual Studio Code (VS Code).

Although there are currently experiment tracking tools available, they are separate services. Whereas, Iterative aims to bring everything together into a one-stop shop. The DVC extension enables data scientists to manage their data, run and track experiments, create plots, and view metrics from their IDE.

“The purpose of the extension is to provide for experiment tracking right on your code editor for VS Code,” adds Petrov.

Key highlights from this video interview are:

  • There are currently experiment tracking tools available, both open source and proprietary, but they are a separate service. Petrov explains why having the DVC Extension for VS Code improves the development experience. He takes Swapnil through the key features of the open source extension.
  • Petrov believes that having a shorter feedback loop and being able to choose the development environment, whether in the cloud or local machine, help create a great experiment tracking experience. He takes a deep dive into the main reasons why he feels the extension was needed.
  • Petrov discusses the benefits of DVC extension for data scientists and the value it brings, such as a quick feedback loop, and having a system that automatically tracks all the experiments automatically.

Connect with Dmitry Petrov (LinkedIn, Twitter)

The summary of the show is written by Emily Nicholls.

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