Hi everyone, I'm a new prefect user and I am trying to use prefect to automate ml pipelines. I went through prefect website documentation tutorials but there's not so much content that goes in depth or touch on MLOps concepts. Can anyone point me to a good introductory resource where I can learn how to use prefect for machine learning models automation and deployment?

it’s hard to give a clear pointer because MLOps is such a broad and loaded term. What specifically do you try to do and have issues with? In general, Prefect can orchestrate for you anything you can write in Python - whether this is ML model training, exploratory data analysis, ETL/ELT data pipelines, persisting results of ML experiments, etc. I will point you to resources I’m aware of that may be helpful: • https://www.datarevenue.com/en-blog/what-we-are-loving-about-prefect • https://medium.com/the-prefect-blog/the-simple-guide-to-productionizing-data-workflows-with-docker-31a5aae67c0a •

You can look at well at this repository which is building an mlops open source platform with perfect https://github.com/datarevenue-berlin/OpenMLOps

Thank you so much @Anna Geller and @davzucky, the repo mentioned above have the information to get me started. Thank you🙏