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Trevor Bye
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articles/machine-learning/service/tutorial-pipeline-batch-scoring-classification.md

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# Use Azure Machine Learning Pipelines for batch scoring
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In this tutorial, you use Azure Machine Learning service pipelines to run a batch scoring, or inference, job. This example job uses the pre-trained [Inception-V3](https://arxiv.org/abs/1512.00567) convolutional neural network Tensorflow model to classify unlabeled images. After building and publishing a pipeline, you'll configure a REST endpoint so you can trigger the pipeline from any HTTP library on any platform.
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In this tutorial, you use Azure Machine Learning service pipelines to run a batch scoring job. This example job uses the pre-trained [Inception-V3](https://arxiv.org/abs/1512.00567) convolutional neural network Tensorflow model to classify unlabeled images. After building and publishing a pipeline, you configure a REST endpoint so you can trigger the pipeline from any HTTP library on any platform.
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Machine learning pipelines optimize your workflow with speed, portability, and reuse so you can focus on your expertise, machine learning, rather than on infrastructure and automation. [Learn more about ML pipelines](concept-ml-pipelines.md).
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