## Azure Machine Learning service training examples

These examples show you:

1. [How to use the Estimator pattern in Azure ML](how-to-use-estimator)
2. [Train using TensorFlow Estimator and tune hyperparameters using Hyperdrive](train-hyperparameter-tune-deploy-with-tensorflow)
3. [Train using Pytorch Estimator and tune hyperparameters using Hyperdrive](train-hyperparameter-tune-deploy-with-pytorch)
4. [Train using Keras and tune hyperparameters using Hyperdrive](train-hyperparameter-tune-deploy-with-keras)
5. [Train using Chainer Estimator and tune hyperparameters using Hyperdrive](train-hyperparameter-tune-deploy-with-chainer)
6. [Distributed training using TensorFlow and Parameter Server](distributed-tensorflow-with-parameter-server)
7. [Distributed training using TensorFlow and Horovod](distributed-tensorflow-with-horovod)
8. [Distributed training using Pytorch and Horovod](distributed-pytorch-with-horovod)
9. [Distributed training using CNTK and custom Docker image](distributed-cntk-with-custom-docker)
10. [Distributed training using Chainer](distributed-chainer)
11. [Export run history records to Tensorboard](export-run-history-to-tensorboard)
12. [Use TensorBoard to monitor training execution](tensorboard)
13. [Resuming training from previous run](train-tensorflow-resume-training)

Learn more about how to use `Estimator` class to  [train deep neural networks with Azure Machine Learning](https://docs.microsoft.com/azure/machine-learning/service/how-to-train-ml-models).

 ![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/MachineLearningNotebooks/how-to-use-azureml/training-with-deep-learning/README.png)