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Using basic training APIs

Follow these sample notebooks to learn:

  1. 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 a model using local computer as compute target.
  3. Train on remote VM: train a model using a remote Azure VM as compute target.
  4. Train on AmlCompute: train a model using an AmlCompute cluster as compute target.
  5. Train in an HDI Spark cluster: train a Spark ML model using an HDInsight Spark cluster as compute target.
  6. Logging API: experiment with various logging functions to create runs and automatically generate graphs.

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