Use the Experiment
Manager app to find optimal training options for neural networks by
sweeping through a range of hyperparameter values or by using Bayesian
optimization. Use the built-in function
define your own custom training function.
Test different training configurations at the same time by running your
experiment in parallel. Offload experiments as batch jobs in a remote
cluster so that you can continue working or close your MATLAB® session while your experiment is running. Monitor your progress by using training plots. Use confusion
matrices and custom metric functions to evaluate your trained network.
Use visualizations, filters, and annotations to manage your experiment results and
record your observations. Access past experiment definitions to keep track
of the combinations of hyperparameters that produce each of your results.
|Design and run experiments to train and compare deep learning networks (Since R2020a)
|Update results table and training plots for custom training experiments (Since R2021a)
- Create a Deep Learning Experiment for Classification
Train a deep learning network for classification using Experiment Manager. (Since R2020a)
- Create a Deep Learning Experiment for Regression
Train a deep learning network for regression using Experiment Manager. (Since R2020a)
- Use Experiment Manager to Train Networks in Parallel
Run multiple simultaneous trials or one trial at a time on multiple workers. (Since R2020b)
- Offload Deep Learning Experiments as Batch Jobs to a Cluster
Run experiments on a cluster so you can continue working or close MATLAB. (Since R2022a)
- Evaluate Deep Learning Experiments by Using Metric Functions
Use metric functions to evaluate the results of an experiment. (Since R2020a)
- Tune Experiment Hyperparameters by Using Bayesian Optimization
Find optimal network hyperparameters and training options for convolutional neural networks. (Since R2020b)
- Use Bayesian Optimization in Custom Training Experiments
Create custom training experiments that use Bayesian optimization. (Since R2021b)
- Generate Experiment Using Deep Network Designer
Use Experiment Manager to tune the hyperparameters of a network trained in Deep Network Designer.
- Keyboard Shortcuts for Experiment Manager
Navigate Experiment Manager using only your keyboard.
Diagnose problems in your setup, training, and metric functions. (Since R2023a)