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Open Source MLOPs

By Matthew Upson
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COMING SOON! Publishing on 03 March 2025
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50+ new titles added every month on new and emerging tech
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This book & 6500+ ebooks & video courses on 1000+ technologies
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50+ new titles added every month on new and emerging tech
Early Access to eBooks as they are being written
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Customised display settings for better reading experience
50+ new titles added every month on new and emerging tech
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Download this book in EPUB and PDF formats
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About this book
The process of deriving useful insights from machine learning can be an arduous, though rewarding, one, even for data science practitioners. It’s worth investing in any tools or techniques that can assist with the process. Open Source MLOPs with DVC and CML will take you through two such techniques, which will allow you to automate your machine learning pipelines and make them eminently reproducible. You'll begin with an introduction to Data Version Control (DVC) and learn how it can help you keep track of your machine learning artifacts using a familiar Git-like approach. This will lead you on to building end-to-end machine learning pipelines, complete with visualizations of the results. We move on to Continuous Machine Learning (CML), with which you can automate the training and testing of machine learning models so they can run alongside the rest of your CI/CD pipeline, ensuring stability and reproducibility. By the end of this book, you will be able to develop reproducible pipelines as directed acyclic graphs and run those pipelines effortlessly in the cloud to speed up the development of your machine learning models.
Publication date:
03 March 2025
Publisher
Packt
ISBN
9781801813204

About the Author
  • Matthew Upson

    Matthew Upson is a Data Scientist and Founder of MantisNLP experienced in Natural Language Processing and Machine Learning / Data Engineering problems. Previously he was the Lead Data Scientist at Juro, a legal tech startup where he used AI to make contracts faster, smarter, and more human. Prior to working at Juro he worked as a Data Scientist in the UK Government predominantly on Machine Learning services for Natural Language Processing. Version Control, Continuous integration, and Cloud Computing.

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