msaroufim/ml-design-patterns

Software Architecture for ML engineers

32
/ 100
Emerging

This project offers blueprints for structuring machine learning applications, helping ML engineers build robust systems. It provides patterns for managing sequential data processing, orchestrating complex multi-step workflows, handling model inputs and outputs efficiently, and enabling event-driven actions during training or inference. ML engineers can use these patterns to design more scalable and maintainable solutions.

418 stars. No commits in the last 6 months.

Use this if you are an ML engineer looking for architectural guidance and common solutions to structuring various components of your machine learning applications, from data pipelines to model serving.

Not ideal if you are looking for ready-to-use libraries or frameworks, as this project focuses on conceptual design patterns rather than direct implementation.

MLOps Model Deployment Data Preprocessing Workflow Orchestration ML System Design
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 14 / 25

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418

Forks

32

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Last pushed

Jun 29, 2022

Commits (30d)

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