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docs: Add detailed use case sections for training, inference, and MLOps
Add comprehensive documentation extracted from V3 example notebooks covering all training, inference, and MLOps use cases with V3 code examples. New sections include local container training, distributed training, hyperparameter management, JumpStart, custom InferenceSpec, model optimization, inference pipelines, processing jobs, batch transform, model registry, Clarify, EMR Serverless, MLflow integration, and lineage tracking. Each section includes red NEW highlights for change detection and expanded V2-to-V3 migration tables.
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docs/_static/custom.css

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docs/ml_ops/index.rst

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E2E Pipeline with Model Registry
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Processing Jobs
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Batch Transform Jobs
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Hyperparameter Tuning
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Model Registry
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Clarify Bias and Explainability
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EMR Serverless Pipeline Step
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MLflow Integration
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MLOps Classes and Imports
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V3 Package Structure
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