Tune Deep Neural Networks
Programmatically and interactively tune training options, resume training from a checkpoint, and investigate adversarial examples
To learn how to set options using the trainingOptions
function, see Set Up Parameters and Train Convolutional Neural Network. After you identify some good starting options, you can automate sweeping of hyperparameters or try Bayesian optimization using Experiment Manager. Use Experiment Manager to test different training configurations at the same time by running your experiment in parallel and monitor your progress by using training plots.
Catégories
- Experiment Manager App
Train networks under multiple initial conditions, interactively tune training options, and assess your results
- Tuning
Programmatically tune training options, resume training from a checkpoint, and investigate adversarial examples