mlops-zoomcamp
huggingface-demos
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mlops-zoomcamp
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Where do I start to learn MLOPS?
There is MLOps Zoomcamp course (which shows end-to-end MLOps process with open-source MLOps tools) https://github.com/DataTalksClub/mlops-zoomcamp.
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MLOps level 4 tooling
Yes, your point exact. I haven't found any quality ones to be honest. There is the coursera mlops course (i did complete this one) which covers tfx (and other services like kubeflow but only scratching the surface) but that seems to be an overkill for me and also very dependant on tensorflow. I have came across this lately https://github.com/DataTalksClub/mlops-zoomcamp (havent went through it in detail) which seems to cover a lot but still missing both the full picture example and i dont see e.g. A/B testing, canary there
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How to start with MLops
datatalksclub https://github.com/DataTalksClub/mlops-zoomcamp
- As an engineer moving into the DS field, I got my first job offer. Does it sound reasonable?
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MLOps Zoomcamp from DataTalks.Club 2023
DataTalksClub/mlops-zoomcamp: Free MLOps course from DataTalks.Club (github.com)
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What are some of the best courses to learn MLOps?
I found this one and also online events hosted by the MLOps community.
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MLOps classes recommendations (not theory behind how to build models, but on deployment and monitoring)
I think this course is a great one for practical MLOps. They have video lectures with homework https://github.com/DataTalksClub/mlops-zoomcamp
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Books & Resources on MLOps on DL on Edge
This is one of the possible resources online https://github.com/DataTalksClub/mlops-zoomcamp. It's a free course. And I also know that the MLOps community hosts many events around the topic.
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Looking for a python study partner, focusing on ML/AI and mlops
I had seen a GitHub which uses like popular open source projects to build an end to end ml lifecycle. Im planning to follow it. https://github.com/DataTalksClub/mlops-zoomcamp
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How do you build CI/CD pipelines for ML projects?
Maybe this will help https://github.com/DataTalksClub/mlops-zoomcamp
huggingface-demos
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Where do I start to learn MLOPS?
At FourthBrain we've recently been hosting a number of public events that try to help guide you step-by-step with code along the path of best practices in MLOps, including one with Hugging Face on end-to-end MLOps (GitLab code here) and one with Databricks on model version control with MLflow (GitHub code here).
What are some alternatives?
data-engineering-zoomcamp - Free Data Engineering course!
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
software-dev-for-mlops-101 - Set up your local environment to do some real Machine Learning Operations software development, just like pro MLOps practitioners.
fake-s3 - A lightweight server clone of Amazon S3 that simulates most of the commands supported by S3 with minimal dependencies
20220726_Databricks_Demo_Transfer_Learning_with_MLflow - We will go hands-on with an image classification demo using transfer learning, while leveraging MLflow to track our model experiments on Databricks
mlbookcamp-code - The code from the Machine Learning Bookcamp book
awesome-mlops - A curated list of references for MLOps
you-dont-need-a-bigger-boat - An end-to-end implementation of intent prediction with Metaflow and other cool tools
mlflow-deployments - Source code for the post Effortless deployments with MLFlow, showcasing how logging models using MLFLow can provide you want to easily deploy them in production later.
mlcomops