awesome-mlops

A curated list of references for MLOps (by visenger)
Add to my DEV experience Machine Learning Mlops Data Science Engineering federated-learning DevOps software-engineering AI ML
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ml-ops.org
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Awesome-mlops Alternatives

Similar projects and alternatives to awesome-mlops

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better awesome-mlops alternative or higher similarity.
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awesome-mlops reviews and mentions

Posts with mentions or reviews of awesome-mlops. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-07.
  • MLOps
    1 project | news.ycombinator.com | 16 Apr 2023
  • ML Engineer Roadmap
    1 project | /r/datascience | 11 Apr 2023
    I'm in the same boat. Data scientist shifting towards ML engineering-MLOps. The guide seems quite complete. I am also doing the ML DevOps engineer, which has end-to-end projects and has been helpful so far. I also feel that most ML engineers will be Mlops too, as most companies will not distinguish between the two, so I try to focus on this part. Here is a quite comprehensive list of resources: https://github.com/visenger/awesome-mlops
  • Mlops roadmap
    3 projects | /r/mlops | 7 Apr 2023
    Good Reference: https://github.com/visenger/awesome-mlops (The Link above has so many Guides, It's insane) https://madewithml.com/
  • What do data scientists use Docker for?
    1 project | /r/datascience | 1 Apr 2023
  • Do you wonder why MLOps is not at the same level as DevOps?
    2 projects | /r/MLQuestions | 31 Mar 2023
    I recently did a deep-dive into MLOps for a client, and I've found that https://ml-ops.org/ offers a great overview. Some topics are a bit too "zoomed out", but they still touch on most important aspects of building an end-to-end product. I found it a great starting point when doing research, and picking and choosing some key points from each section + some google helped a lot. Give it a look, you'll probably find some useful things in there.
  • Can you guys explain to me what MLOps is?
    1 project | /r/dataengineering | 20 Mar 2023
  • MLOps on GitHub Actions with Cirun
    3 projects | dev.to | 29 Dec 2022
    MLOps
  • DevOps - where to begin?
    3 projects | /r/datascience | 16 Aug 2022
  • JBCNConf 2022: A great farewell
    6 projects | dev.to | 23 Jul 2022
    She made mentions to ML-Ops and MLFlow including Vertex AI the GCP implementation. I will post the video as soon as it is available. In the meantime, you can enjoy any other talk from Nerea Luis
  • Can Mechanical Engineers become MLOps?
    2 projects | /r/mlops | 25 Apr 2022
    From your post, you seem to be trained for data science for physics modeling, so I'd recommend to get started with https://ml-ops.org/ and for the data engineering part, I found this https://github.com/andkret/Cookbook open source cookbook to be invaluable.
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    www.influxdata.com | 8 May 2024
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Stats

Basic awesome-mlops repo stats
24
11,769
5.2
15 days ago

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