# MLOps

## Using AntiPatterns to avoid MLOps Mistakes

{% embed url="<https://aiden-jeon.github.io/post/tech/mlops/antipatterns_for_mlops/?fbclid=IwAR3CTs0pni8Rf-PEEAbLGRaCxTeR7O3pMxrPh30S-Vql9RVtPja0MjFNzc4>" %}

{% embed url="<https://arxiv.org/abs/2107.00079?fbclid=IwAR225Wdeb43E1ENZTd5pGkLGG-FrnvmJCs6cLw6aB-uDQUalbDI3KM-8uoo>" %}

## CI/CD for ML Online Serving and Models (Uber)

{% embed url="<https://eng.uber.com/continuous-integration-deployment-ml/?fbclid=IwAR2He_5BZWLceI_NKVZRxLgw0ETzFC5xPXh-rvk8Q1LBuyHDOvOOX3Rw0T0>" %}

## Machine Learning Engineering for Production

Panel discussion introducing a new specialization for MLOps

{% embed url="<https://www.youtube.com/watch?v=Ta14KpeZJok>" %}

## MLOps KR Seminar

{% embed url="<https://www.youtube.com/watch?v=eQzjJ5fTlKU&list=PLIuC6QlQQF0Pf-aM0tioYTjrnLzaJaGez&index=6>" %}

## Practical MLOps eBook

{% embed url="<https://valohai.com/assets/files/practical-mlops-ebook.pdf>" %}

Translated in Korean

{% embed url="<https://drive.google.com/drive/folders/1gNqgfOJvdqc6q9Hn1ctwWwoZNjLfHEE2>" %}