MLOps References

MLOpsRefs.md

MLOps Cafe References

Date: 20221006

Introduction

• MLOps Explained: https://www.youtube.com/watch?v=ZVWg18AXXuE
• MLOps Continuous delivery and automation pipelines in machine learning: https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning
• Your First MLOps (pipeline): https://www.linkedin.com/video/event/urn:li:ugcPost:6952875868721426432/
• AI Infrastructure Ecosystem: https://ai-infrastructure.org/ai-infrastructure-ecosystem-report-of-2022/

Data Versioning

• DVC & MLFlow: https://www.youtube.com/watch?v=W2DvpCYw22o

Data Validation

• Great Expecations: https://www.digitalocean.com/community/tutorials/how-to-test-your-data-with-great-expectations
• Deep Check: https://docs.deepchecks.com/stable/getting-started/welcome.html
• Evidently AI: https://www.youtube.com/watch?v=L4Pv6ExBQPM

Experiment Tracking

• MLFlow: https://www.youtube.com/watch?v=IUF4s9SXnd4

Model Serving

• MLFlow & Seldon: https://www.youtube.com/watch?v=fmwyQjfL26k

Model Monitoring

• Model Monitoring & Serving: https://fullstackdeeplearning.com/spring2021/lecture-11/
• Concept Drift: https://www.aporia.com/blog/concept_drift_in_machine_learning_101/
• Alibi-detect: https://github.com/SeldonIO/alibi-detect

Pipelines

• SageMaker: https://sagemaker-examples.readthedocs.io/en/latest/index.html , https://www.youtube.com/watch?v=sL8wpFo7LaQ
• MLFlow: https://www.youtube.com/watch?v=IUF4s9SXnd4
• ZenML: https://www.youtube.com/watch?v=EVueQ8zq4eE

Tools

• https://kedro.org/
• Data Annotation : https://www.v7labs.com/
• Video/Image Annotation : https://labelbox.com/

Coureses

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp