If you are new to HPE Machine Learning Development Environment, find out how to Create Your First Experiment. For a deeper dive, visit the Quickstart for Model Developers where you’ll learn how to perform the following tasks:

  • Train on a local, single CPU or GPU.

  • Run a distributed training job on multiple GPUs.

  • Use hyperparameter tuning.

Get Started with a Trial API#

To get started with a Trial API, visit PyTorch MNIST Tutorial. This tutorial shows you how to port a simple image classification model for the MNIST dataset.

Train Your Model in HPE Machine Learning Development Environment#

Training API Guides include the Core API User Guide and walk you through how to take your existing model code and train your model in HPE Machine Learning Development Environment.

Try an Example#

Examples let you build off of an existing model that already runs on HPE Machine Learning Development Environment. Visit our Examples to see if the model you’d like to train is already available.