[D] Resources on MLE and MLOps?

Hi all,

I'll be starting an internship as an MLE next month. I already have experience with ML, so I'm looking for recommendations on the *engineering* side of MLE: how to design, maintain, and improve production ML systems.

Currently I have found some interesting resources:

* [Chip Huyen's Designing ML Systems](https://www.amazon.com.br/Designing-Machine-Learning-Systems-English-ebook/dp/B0B1LGL2SR)
* [Andriy Burkov's Machine Learning Engineering](https://www.amazon.com/Machine-Learning-Engineering-Andriy-Burkov/dp/1999579577)
* [Andrew Ng's course on MLOps](https://www.coursera.org/specializations/machine-learning-engineering-for-production-mlops)

Do you have any experiences with these resources or other recommendations to share? Thanks in advance! :)

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