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147 | 147 | - name: Train with SDK v1
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148 | 148 | href: how-to-attach-compute-targets.md
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149 | 149 | - name: Automated machine learning
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150 |
| - displayName: automl, auto ml |
151 |
| - items: |
152 |
| - - name: Use automated ML (Python) |
153 |
| - displayName: SDK, automl |
154 |
| - href: how-to-configure-auto-train-v1.md |
155 |
| - - name: Auto-train a regression (NYC Taxi data) |
156 |
| - displayName: automl, automated, auto ml, |
157 |
| - href: how-to-auto-train-models-v1.md |
158 |
| - - name: Auto-train object detection model |
159 |
| - displayName: auto ML, automl, CLI |
160 |
| - href: tutorial-auto-train-image-models-v1.md |
161 |
| - - name: Auto-train a natural language processing model |
162 |
| - displayName: nlp, auto ML, automl, SDK |
163 |
| - href: how-to-auto-train-nlp-models-v1.md |
164 |
| - - name: Set up AutoML to train computer vision models with Python |
165 |
| - displayName: auto ML, automl, SDK |
166 |
| - href: how-to-auto-train-image-models-v1.md |
167 |
| - - name: Local inference using ONNX |
168 |
| - displayName: SDK, automl |
169 |
| - href: how-to-inference-onnx-automl-image-models-v1.md |
170 |
| - - name: Track experiments with MLflow |
171 |
| - displayName: log, monitor, metrics, model registry, register |
172 |
| - href: how-to-use-mlflow.md |
| 150 | + displayName: automl, auto ml |
| 151 | + items: |
| 152 | + - name: Use automated ML (Python) |
| 153 | + displayName: SDK, automl |
| 154 | + href: how-to-configure-auto-train-v1.md |
| 155 | + - name: Auto-train a regression (NYC Taxi data) |
| 156 | + displayName: automl, automated, auto ml, |
| 157 | + href: how-to-auto-train-models-v1.md |
| 158 | + - name: Auto-train object detection model |
| 159 | + displayName: auto ML, automl, CLI |
| 160 | + href: tutorial-auto-train-image-models-v1.md |
| 161 | + - name: Auto-train a natural language processing model |
| 162 | + displayName: nlp, auto ML, automl, SDK |
| 163 | + href: how-to-auto-train-nlp-models-v1.md |
| 164 | + - name: Set up AutoML to train computer vision models with Python |
| 165 | + displayName: auto ML, automl, SDK |
| 166 | + href: how-to-auto-train-image-models-v1.md |
| 167 | + - name: Local inference using ONNX |
| 168 | + displayName: SDK, automl |
| 169 | + href: how-to-inference-onnx-automl-image-models-v1.md |
| 170 | + - name: Track experiments with MLflow |
| 171 | + displayName: log, monitor, metrics, model registry, register |
| 172 | + href: how-to-use-mlflow.md |
173 | 173 |
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174 | 174 | - name: Interpret ML models
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175 | 175 | displayName: SDK, interpret, explain, explainability, interpretability
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