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Merge pull request #113698 from MicrosoftDocs/j-martens-patch-16
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articles/machine-learning/toc.yml

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items:
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- name: Plan and manage costs
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href: concept-plan-manage-cost.md
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- name: Designer (drag-n-drop ML)
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items:
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- name: Designer overview
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displayName: studio
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href: concept-designer.md
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- name: Algorithm cheat sheet
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href: /azure/machine-learning/algorithm-cheat-sheet
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- name: How to select algorithms
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href: /azure/machine-learning/how-to-select-algorithms
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- name: Automated ML
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displayName: automl, auto ml
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href: concept-automated-ml.md
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- name: Workspace
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href: concept-workspace.md
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- name: Environments
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href: concept-environments.md
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- name: Data ingestion
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href: concept-data-ingestion.md
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- name: Data access
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href: concept-data.md
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- name: Compute instance
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displayName: resource, dsvm, Data Science Virtual Machine
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href: concept-compute-instance.md
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- name: Compute target
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displayName: resource, dsvm, AKS, kubernetes, amlcompute, Data Science Virtual Machine, local, cluster, ACI, container instance, ADB, Databricks, data lake, lake, HDI, HDInsight
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href: concept-compute-target.md
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- name: Data
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items:
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- name: Data access
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href: concept-data.md
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- name: Data ingestion
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href: concept-data-ingestion.md
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- name: Common pitfalls
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displayName: automl, auto ml, risks
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href: concept-manage-ml-pitfalls.md
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- name: Model training
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displayName: run config, estimator, machine learning pipeline, ml pipeline, train model
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href: concept-train-machine-learning-model.md
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- name: Distributed training
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displayName: parallellization, deep learning, deep neural network, dnn
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href: concept-distributed-training.md
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- name: Deep learning
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displayName: deep learning vs machine learning, deep learning, vs, versus
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href: concept-deep-learning-vs-machine-learning.md
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- name: Model management (MLOps)
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displayName: deploy, deployment, publish, production, operationalize, operationalization
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href: concept-model-management-and-deployment.md
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- name: Interpretability
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- name: Model portability (ONNX)
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href: concept-onnx.md
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- name: Model interpretability
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displayName: explainability
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href: how-to-machine-learning-interpretability.md
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- name: "Designer: no-code ML"
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displayName: studio
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href: concept-designer.md
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- name: Algorithm cheat sheet
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href: /azure/machine-learning/algorithm-cheat-sheet
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- name: How to select algorithms
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href: /azure/machine-learning/how-to-select-algorithms
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- name: Automated ML
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displayName: automl, auto ml
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href: concept-automated-ml.md
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- name: Overfitting & imbalanced data
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displayName: automl, auto ml, risks
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href: concept-manage-ml-pitfalls.md
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- name: Compute instance
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displayName: resource, dsvm, Data Science Virtual Machine
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href: concept-compute-instance.md
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- name: Compute target
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displayName: resource, dsvm, AKS, kubernetes, amlcompute, Data Science Virtual Machine, local, cluster, ACI, container instance, ADB, Databricks, data lake, lake, HDI, HDInsight
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href: concept-compute-target.md
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- name: ML pipelines
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href: concept-ml-pipelines.md
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- name: ONNX
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href: concept-onnx.md
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- name: Enterprise readiness & security
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items:
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- name: Enterprise security
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href: monitor-azure-machine-learning.md
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- name: Event grid integration
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href: concept-event-grid-integration.md
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- name: Deep learning
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displayName: deep learning vs machine learning, deep learning, vs, versus
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href: concept-deep-learning-vs-machine-learning.md
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- name: How-to guides
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items:
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- name: Create & manage workspaces

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