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Automate hyperparameter optimization training with the Watson Machine Learning Accelerator API

About this video

In this video, see how to submit a model and data set to the Watson Machine Learning Accelerator API to run hyperparameter optimization, or HPO. You use the Pytorch MNIST HPO as the training model, inject hyperparameters for the sub-training during search, submit a tuning metric for better results, then query for the best job results.

To view other videos related to Watson Machine Learning Accelerator, see Videos.