update samples from Release-69 as a part of SDK release
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@@ -16,6 +16,7 @@ The following tutorials are intended to provide an introductory overview of Azur
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| Tutorial | Description | Notebook | Task | Framework |
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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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