|
7 | 7 | - name: Architecture & terms
|
8 | 8 | displayName: architecture, concepts, definitions, glossary
|
9 | 9 | href: concept-azure-machine-learning-architecture.md
|
10 |
| - |
11 | 10 | - name: Upgrade to SDK v2
|
12 | 11 | items:
|
13 | 12 | - name: Upgrade overview
|
|
53 | 52 | - name: "Migrate endpoints"
|
54 | 53 | displayName: migration, v1, v2
|
55 | 54 | href: ../migrate-to-v2-deploy-endpoints.md
|
56 |
| -- name: Concepts (v1) |
57 |
| - items: |
58 |
| - - name: Model training |
59 |
| - displayName: run config, machine learning pipeline, ml pipeline, train model |
60 |
| - href: concept-train-machine-learning-model-v1.md |
61 |
| - - name: Work with data |
62 |
| - items: |
63 |
| - - name: Data access |
64 |
| - href: concept-data.md |
65 |
| - - name: Studio network data access |
66 |
| - href: concept-network-data-access.md |
67 |
| - - name: Automated ML overview |
68 |
| - displayName: automl, auto ml |
69 |
| - href: concept-automated-ml-v1.md |
70 |
| - - name: Manage the ML lifecycle (MLOps) |
71 |
| - items: |
72 |
| - - name: MLOps capabilities |
73 |
| - displayName: deploy, deployment, publish, production, operationalize, operationalization |
74 |
| - href: concept-model-management-and-deployment.md |
75 |
| - - name: MLflow |
76 |
| - href: concept-mlflow-v1.md |
77 |
| - - name: Manage resources VS Code |
78 |
| - displayName: vscode,resources |
79 |
| - href: ../how-to-manage-resources-vscode.md |
80 |
| - - name: Git integration |
81 |
| - displayName: github gitlab |
82 |
| - href: ../concept-train-model-git-integration.md |
83 | 55 | - name: Tutorials (v1)
|
84 | 56 | expanded: true
|
85 | 57 | items:
|
|
110 | 82 | - name: Examples repository
|
111 | 83 | displayName: example, examples, jupyter, python, notebook, github
|
112 | 84 | href: https://github.com/azure/machinelearningnotebooks
|
| 85 | +- name: Concepts (v1) |
| 86 | + items: |
| 87 | + - name: Model training |
| 88 | + displayName: run config, machine learning pipeline, ml pipeline, train model |
| 89 | + href: concept-train-machine-learning-model-v1.md |
| 90 | + - name: Work with data |
| 91 | + items: |
| 92 | + - name: Data access |
| 93 | + href: concept-data.md |
| 94 | + - name: Studio network data access |
| 95 | + href: concept-network-data-access.md |
| 96 | + - name: Automated ML overview |
| 97 | + displayName: automl, auto ml |
| 98 | + href: concept-automated-ml-v1.md |
| 99 | + - name: Manage the ML lifecycle (MLOps) |
| 100 | + items: |
| 101 | + - name: MLOps capabilities |
| 102 | + displayName: deploy, deployment, publish, production, operationalize, operationalization |
| 103 | + href: concept-model-management-and-deployment.md |
| 104 | + - name: MLflow |
| 105 | + href: concept-mlflow-v1.md |
| 106 | + - name: Manage resources VS Code |
| 107 | + displayName: vscode,resources |
| 108 | + href: ../how-to-manage-resources-vscode.md |
| 109 | + - name: Git integration |
| 110 | + displayName: github gitlab |
| 111 | + href: ../concept-train-model-git-integration.md |
113 | 112 | - name: Infrastructure & security (v1)
|
114 | 113 | items:
|
115 | 114 |
|
|
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