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MLOps track

Model Versioning

Model artifacts, semantic versions and provenance.

6 concepts3 labs1 challenges
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Concepts

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Work through the concepts in order, or jump to what you need.

1

Why Version Models

Concept · Hands-on lab included

2

Artifact Serialization Formats

Concept · Hands-on lab included

3

Semantic Versions for Models

Concept · Hands-on lab included

4

Binaries and Signatures

Concept · Hands-on lab included

5

Metadata and Lineage

Concept · Hands-on lab included

6

Rollback and Multi-Version Serving

Concept · Hands-on lab included

Practice

Hands-on labs

Apply what you've learned in guided, production-style environments.

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Wrap a Model with an Enforced Signature

25 min · intermediate · Binaries and Signatures

Capture and Query Model Lineage

25 min · advanced · Metadata and Lineage

Route and Roll Back Between Versions

30 min · advanced · Rollback and Multi-Version Serving

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Next modules

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ML Lifecycle

The full ML lifecycle and the operational discipline MLOps adds.

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Experiment Tracking

MLflow tracking, run metadata, reproducibility and comparing experiments.

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Dataset Versioning

DVC, data lineage and immutability for training data.

DevOpsForge - MLOps · Model Versioning
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