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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.

Categories

  • Manage Experiments
    Train networks under multiple initial conditions, interactively tune training options, and evaluate your results
  • Tuning
    Programmatically tune training options, resume training from a checkpoint, and investigate adversarial examples