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Merge pull request #250 from changeworld/patch-3
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articles/machine-learning/how-to-create-component-pipeline-python.md

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### Create the score-model component
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In this section, other than the previous components, you'll create a component to score the trained model via Yaml specification and script.
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In this section, other than the previous components, you'll create a component to score the trained model via YAML specification and script.
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If you're following along with the example in the [Azure Machine Learning examples repo](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/pipelines/2e_image_classification_keras_minist_convnet), the source files are already available in `score/` folder. This folder contains three files to construct the component:
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The code in score.py takes three command-line arguments: `input_data`, `input_model` and `output_result`. The program score the input model using input data and then output the scoring result.
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#### Define component via Yaml
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#### Define component via YAML
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In this section, you'll learn to create a component specification in the valid YAML component specification format. This file specifies the following information:
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articles/machine-learning/reference-automl-images-cli-instance-segmentation.md

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## YAML syntax
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For information on all the keys in Yaml syntax, see [Yaml syntax](./reference-automl-images-cli-classification.md#yaml-syntax) of image classification task. Here we only describe the keys that have different values as compared to what's specified for image classification task.
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For information on all the keys in YAML syntax, see [YAML syntax](./reference-automl-images-cli-classification.md#yaml-syntax) of image classification task. Here we only describe the keys that have different values as compared to what's specified for image classification task.
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| Key | Type | Description | Allowed values | Default value |
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| --- | ---- | ----------- | -------------- | ------------- |

articles/machine-learning/reference-automl-images-cli-multilabel-classification.md

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## YAML syntax
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For information on all the keys in Yaml syntax, see [Yaml syntax](./reference-automl-images-cli-classification.md#yaml-syntax) of image classification task. Here we only describe the keys that have different values as compared to what's specified for image classification task.
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For information on all the keys in YAML syntax, see [YAML syntax](./reference-automl-images-cli-classification.md#yaml-syntax) of image classification task. Here we only describe the keys that have different values as compared to what's specified for image classification task.
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| Key | Type | Description | Allowed values | Default value |
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| --- | ---- | ----------- | -------------- | ------------- |

articles/machine-learning/reference-automl-images-cli-object-detection.md

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## YAML syntax
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For information on all the keys in Yaml syntax, see [Yaml syntax](./reference-automl-images-cli-classification.md#yaml-syntax) of image classification task. Here we only describe the keys that have different values as compared to what's specified for image classification task.
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For information on all the keys in YAML syntax, see [YAML syntax](./reference-automl-images-cli-classification.md#yaml-syntax) of image classification task. Here we only describe the keys that have different values as compared to what's specified for image classification task.
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| Key | Type | Description | Allowed values | Default value |
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| --- | ---- | ----------- | -------------- | ------------- |

articles/machine-learning/v1/azure-machine-learning-release-notes.md

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+ **New features**
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+ Introduced FileDataset, which references single or multiple files in your datastores or public urls. The files can be of any format. FileDataset provides you with the ability to download or mount the files to your compute.
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+ Added Pipeline Yaml Support for PythonScript Step, Adla Step, Databricks Step, DataTransferStep, and AzureBatch Step
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+ Added Pipeline YAML Support for PythonScript Step, Adla Step, Databricks Step, DataTransferStep, and AzureBatch Step
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+ **Bug fixes and improvements**
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+ **azureml-automl-core**

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