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articles/machine-learning/concept-automated-ml.md

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@@ -153,27 +153,27 @@ With the Azure automated ML, you choose either a local computer or a remote comp
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The following table shows a summary of features available on local and remote compute targets. Some of these features are available only in an Enterprise workspace.
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|Feature |Local |Remote |Requires Enterprise |
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|Feature |Local |Remote |Requires Enterprise <br/>workspace |
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|---------|---------|---------|---------|
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|Create and run experiments in notebooks ||| |
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|Register and visualize experiment's info and metrics in UI ||| |
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|Forecasting ||||
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|ONNX models ||| |
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|Ensemble iterations ||| |
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|Data streaming (Large data support, up to 100 GB) | |||
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|Subsampling ||| |
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|Data guardrails ||| |
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|Model interpretability (in notebooks) | | | |
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|DNN-based text featurization | | | |
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|Feature Sweeping (or advanced transformers) | ? | ? | |
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|Custom featurizers support | ? | ? | |
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|Feature engineering customization SDK | ? | ? ||
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|Many models training SDK | ? | ? | |
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|Feature engineering customization UI | || |
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|Forecasting ||||
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|Prophet or ARIMA models for forecasting | |||
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|ONNX models ||| |
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|Many models training SDK | ? | ? | |
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|Multiple runs/iterations in parallel | |||
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|Cancel an iteration | || |
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|Continue a run | || |
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|Data streaming (Large data support, up to 100 GB) | |||
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|DNN-based text featurization | |||
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|Feature engineering customization UI | || |
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|Ensemble iterations ||| |
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|Model interpretability (in notebooks) ||||
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|Create and run experiments in studio web experience | |||
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