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articles/machine-learning/how-to-train-keras.md

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> * [v1](v1/how-to-train-keras.md)
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> * [v2 (current version)](how-to-train-keras.md)
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In this article, learn how to run your Keras training scripts using the Azure Machine Learning (AzureML) Python SDK v2.
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In this article, learn how to run your Keras training scripts using the Azure Machine Learning Python SDK v2.
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The example code in this article uses Azure Machine Learning to train, register, and deploy a Keras model built using the TensorFlow backend. The model, a deep neural network (DNN) built with the [Keras Python library](https://keras.io) running on top of [TensorFlow](https://www.tensorflow.org/overview), classifies handwritten digits from the popular [MNIST dataset](http://yann.lecun.com/exdb/mnist/).
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articles/machine-learning/how-to-train-pytorch.md

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> * [v1](v1/how-to-train-pytorch.md)
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> * [v2 (current version)](how-to-train-pytorch.md)
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In this article, you'll learn to train, hyperparameter tune, and deploy a [PyTorch](https://pytorch.org/) model using the Azure Machine Learning (AzureML) Python SDK v2.
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In this article, you'll learn to train, hyperparameter tune, and deploy a [PyTorch](https://pytorch.org/) model using the Azure Machine Learning Python SDK v2.
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You'll use the example scripts in this article to classify chicken and turkey images to build a deep learning neural network (DNN) based on [PyTorch's transfer learning tutorial](https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html). Transfer learning is a technique that applies knowledge gained from solving one problem to a different but related problem. Transfer learning shortens the training process by requiring less data, time, and compute resources than training from scratch. To learn more about transfer learning, see the [deep learning vs machine learning](./concept-deep-learning-vs-machine-learning.md#what-is-transfer-learning) article.
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articles/machine-learning/tutorial-azure-ml-in-a-day.md

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[!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
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Learn how a data scientist uses Azure Machine Learning (AzureML) to train a model, then use the model for prediction. This tutorial will help you become familiar with the core concepts of Azure Machine Learning and their most common usage.
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Learn how a data scientist uses Azure Machine Learning to train a model, then use the model for prediction. This tutorial will help you become familiar with the core concepts of Azure Machine Learning and their most common usage.
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You'll learn how to submit a *command job* to run your *training script* on a specified *compute resource*, configured with the *job environment* necessary to run the script.
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