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MachineLearningNotebooks/how-to-use-azureml/training/README.md
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## Using basic training APIs
Follow these sample notebooks to learn:
1. [Train within notebook](train-within-notebook): train a simple scikit-learn model using the Jupyter kernel and deploy the model to Azure Container Service.
2. [Train on local](train-on-local): train a model using local computer as compute target.
3. [Train on remote VM](train-on-remote-vm): train a model using a remote Azure VM as compute target.
4. [Train on AmlCompute](train-on-amlcompute): train a model using an AmlCompute cluster as compute target.
5. [Train in an HDI Spark cluster](train-in-spark): train a Spark ML model using an HDInsight Spark cluster as compute target.
6. [Logging API](logging-api): experiment with various logging functions to create runs and automatically generate graphs.
![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/MachineLearningNotebooks/how-to-use-azureml/training/README.png)