Keynote Details

ML Summit
The big training event for Machine Learning
October 11 - 13, 2021 | Online April 2022 | Munich

Milecia McGregor

en

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October 8 – 10
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Tuning Hyperparameters for Your Machine Learning Project

When you start exploring multiple model architectures with different hyperparameter values, you need a way to quickly iterate. There are a lot of ways to handle this, but all of them require time and you might not be able to go back to a particular point to resume or restart training.

In this talk, you will learn how you can use DVC experiments to compare training metrics using two methods for tuning hyperparameters: grid search and random search. You’ll learn how to implement checkpoints to keep track of your experiment runs and you’ll see how quickly you can implement this on your existing projects.