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Iterative’s MLEM Aims To Simplify ML Model Management And Deployment | Dmitry Petrov

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In this episode of TFiR Let’s Talk, Swapnil Bhartiya sits down with Dmitry Petrov, Co-Founder and CEO of Iterative.ai, to discuss the recently released machine learning engineering management tool, MLEM. MLEM aims to bridge the gap between ML engineers and DevOps teams by using the Git-based approach that developers are familiar with.

In discussing the need to break silos between ML teams and DevOps teams, Petrov says, “We need to break this wall, and the way how it can be done is we need to give tools which are compatible with both software development stacks. But basically, we don’t want to manage two different stacks for software developers, for DevOps, and a different technology stack for AI vault, for machine learning engineers, for data scientists.”

Key highlights from this video interview are:

  • MLEM is an open source Git-based tool needed for model management and deployment. It enables users to save their model and then deploy it to some deployment platform like SageMaker.
  • Petrov discusses how MLEM is helping to build a model registry on top of the Git repository and better understanding models and helping the deployment system to deploy them. He goes into detail about these benefits and how MLEM is helping to solve these challenges.
  • Petrov explains who MLEM by Iterative is targeting with the product, such as machine learning teams and DevOps teams, and others who are responsible for the life cycle of the models.
  • MLEM aims to bridge the gap between machine learning engineers and DevOps teams. Petrov goes into the silos of ML teams building models that the DevOps teams then need to deal with. He explains why it is important to break down those walls and how MLEM is helping tackle these problems.
  • Petrov explains the reasons why they decided to make MLEM compatible with the software development stack. He describes how it is enabling data scientists to speak the same language as DevOps by giving them a set of commands that simplify this process, while using best practices.
  • MLEM is an open source product, already hosted on GitHub as the company feels strongly about sharing their products so that anyone can use them. Petrov explains how MLEM fits in with its other offerings in DVC Studio.

Connect with Dmitry Petrov (LinkedIn, Twitter)

The summary of the show is written by Emily Nicholls.

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