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36 lines
4.0 KiB
Markdown
# Azure Machine Learning Tutorials
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Azure Machine Learning, a cloud-based environment you can use to train, deploy, automate, manage, and track ML models.
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Azure Machine Learning can be used for any kind of machine learning, from classical ML to supervised, unsupervised, and deep learning.
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This folder contains a collection of Jupyter Notebooks with the code used in accompanying step-by-step tutorials.
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## Set up your environment.
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If you are using an Azure Machine Learning Notebook VM, everything is already set up for you. Otherwise, see the [get started creating your first ML experiment with the Python SDK tutorial](https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-1st-experiment-sdk-setup).
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## Introductory Samples
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The following tutorials are intended to provide an introductory overview of Azure Machine Learning.
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| Tutorial | Description | Notebook | Task | Framework |
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| --- | --- | --- | --- | --- |
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| [Get Started (day1)](https://docs.microsoft.com/azure/machine-learning/tutorial-1st-experiment-sdk-setup-local) | Learn the fundamental concepts of Azure Machine Learning to help onboard your existing code to Azure Machine Learning. This tutorial focuses heavily on submitting machine learning jobs to scalable cloud-based compute clusters. | [get-started-day1](get-started-day1/day1-part1-setup.ipynb) | Learn Azure Machine Learning Concepts | PyTorch
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| [Train your first ML Model](https://docs.microsoft.com/azure/machine-learning/tutorial-1st-experiment-sdk-train) | Learn the foundational design patterns in Azure Machine Learning and train a scikit-learn model based on a diabetes data set. | [tutorial-quickstart-train-model.ipynb](create-first-ml-experiment/tutorial-1st-experiment-sdk-train.ipynb) | Regression | Scikit-Learn
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| [Train an image classification model](https://docs.microsoft.com/azure/machine-learning/tutorial-train-models-with-aml) | Train a scikit-learn image classification model. | [img-classification-part1-training.ipynb](image-classification-mnist-data/img-classification-part1-training.ipynb) | Image Classification | Scikit-Learn
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| [Deploy an image classification model](https://docs.microsoft.com/azure/machine-learning/tutorial-deploy-models-with-aml) | Deploy a scikit-learn image classification model to Azure Container Instances. | [img-classification-part2-deploy.ipynb](image-classification-mnist-data/img-classification-part2-deploy.ipynb) | Image Classification | Scikit-Learn
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| [Deploy an encrypted inferencing service](https://docs.microsoft.com/azure/machine-learning/tutorial-deploy-models-with-aml) |Deploy an image classification model for encrypted inferencing in Azure Container Instances | [img-classification-part3-deploy-encrypted.ipynb](image-classification-mnist-data/img-classification-part3-deploy-encrypted.ipynb) | Image Classification | Scikit-Learn
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| [Use automated machine learning to predict taxi fares](https://docs.microsoft.com/azure/machine-learning/tutorial-auto-train-models) | Train a regression model to predict taxi fares using Automated Machine Learning. | [regression-part2-automated-ml.ipynb](regression-automl-nyc-taxi-data/regression-automated-ml.ipynb) | Regression | Automated ML
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## Advanced Samples
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The following tutorials are intended to provide examples of more advanced feature in Azure Machine Learning.
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| Tutorial | Description | Notebook | Task | Framework |
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| --- | --- | --- | --- | --- |
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| [Build an Azure Machine Learning pipeline for batch scoring](https://docs.microsoft.com/azure/machine-learning/tutorial-pipeline-batch-scoring-classification) | Create an Azure Machine Learning pipeline to run batch scoring image classification jobs | [tutorial-pipeline-batch-scoring-classification.ipynb](machine-learning-pipelines-advanced/tutorial-pipeline-batch-scoring-classification.ipynb) | Image Classification | TensorFlow
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For additional documentation and resources, see the [official documentation site for Azure Machine Learning](https://docs.microsoft.com/azure/machine-learning/).
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