## Azure Machine Learning service Tutorial

Complete these tutorials to learn how to train and deploy models using Azure Machine Learning services and Python SDK. These Notebooks accompany the
two sets of tutorial articles for:

 * [Image classification using MNIST dataset](https://docs.microsoft.com/en-us/azure/machine-learning/service/tutorial-train-models-with-aml)
 * [Regression using NYC Taxi dataset](https://docs.microsoft.com/en-us/azure/machine-learning/service/tutorial-data-prep)

If you are using an Azure Machine Learning Notebook VM, you are all set. Otherwise, run the [configuration Notebook](../configuration.ipynb) notebook first to set up your Azure ML Workspace. Then, run the notebooks in following recommended order.

### Create first ML experiment

* [Part 1](https://docs.microsoft.com/azure/machine-learning/service/tutorial-quickstart-setup): Set up workspace & dev environment
* [Part 2](tutorial-quickstart-train-model.ipynb): Learn the foundational design patterns in Azure Machine Learning service, and train a simple scikit-learn model based on the diabetes data set

### Image classification

 * [Part 1](img-classification-part1-training.ipynb): Train an image classification model with Azure Machine Learning.
 * [Part 2](img-classification-part2-deploy.ipynb): Deploy an image classification model from first tutorial in Azure Container Instance (ACI).

 ### Regression
 * [Part 1](regression-part1-data-prep.ipynb): Prepare the data using Azure Machine Learning Data Prep SDK.
 * [Part 2](regression-part2-automated-ml.ipynb): Train a model using Automated Machine Learning.

 Also find quickstarts and how-tos on the [official documentation site for Azure Machine Learning service](https://docs.microsoft.com/en-us/azure/machine-learning/service/).

![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/MachineLearningNotebooks/tutorials/README.png)