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MLOps Patterns

General Patterns

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  1. Stanford CS329arrow-up-right - CS 329S: Machine Learning Systems Design - the course goes in-depth about how ML systems are built, and how to debug, root cause, monitor, etc.

  2. Metaflow, medium 1arrow-up-right (high level review), 2arrow-up-right (schema), 3arrow-up-right, **4arrow-up-right (amazing), 5arrow-up-right (extra), 6arrow-up-right (loading and storing data docs!)

Patterns in Practice

  1. An MLOps End-to-End system, i.e., "You dont need a bigger boatarrow-up-right", using MetaFlow, Snowflake, DBT, Prefect, Great Expectations, Weights & Biases, Sagemaker, Lambda

  2. A simplistic E2E systemarrow-up-right - Snowflake, DBT, S3, CometML, Reclist, SageMaker.

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