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World Congress 2021 • Jun 28, 2021

DevOps for Machine Learning

Hauke Brammer

Ninety percent of machine learning models never reach production. Close the workflow gap between data science and engineering by adopting an evolutionary MLOps infrastructure.

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Matching moments

5:28 min

Defining MLOps and its role in production systems

Hauke Brammer · World Congress 2023

2:15 min

Bridging the gap between model management and devops

Joy Joy · World Congress 2024

4:19 min

Introduction to DevOps for AI and MLOps

Aarno Aukia · LIVE

3:56 min

Solving application deployment complexities using LLMOps pipelines

Anshul Jindal Anshul Jindal · World Congress 2025

2:48 min

Defining machine learning operations in a fragmented ecosystem

Nico Axtmann · World Congress 2022

4:31 min

Adopting a DevOps culture for machine learning pipelines

Bas Geerdink · LIVE

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Upcoming sessions on this topic

Open session

Engineering AI Strategy: Beyond the Hype

  • Omkar Srivastava

    ADSK

    Engineering Leader

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The Dream Team You Didn't Know You Had - Multi-Model, Multi-Agent, One Software Lifecycle

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Open session

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Decision models for developers who use LLMs

  • Anurag Bhandari

    antelligent

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Your AI Agents Are Bleeding Tokens: Building a Runtime Cost Control Plane for LLMs

  • Aakriti Aggarwal

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