德ep Network Designer
德scription
The德ep Network Designerapp lets you build, visualize, edit, and train deep learning networks. Using this app, you can:
Build, import, edit, and combine networks.
Load pretrained networks and edit them for transfer learning.
View and edit layer properties and add new layers and connections.
Analyze the network to ensure that the network architecture is defined correctly, and detect problems before training.
Import and visualize datastores and image data for training and validation.
Apply augmentations to image classification training data and visualize the distribution of the class labels.
Train networks and monitor training with plots of accuracy, loss, and validation metrics.
Export trained networks to the workspace or to Simulink®.
Generate MATLAB®code for building and training networks and create experiments for hyperparameter tuning using Experiment Manager.
Open the Deep Network Designer App
MATLAB Toolstrip: On theAppstab, underMachine Learning and Deep Learning, click the app icon.
MATLAB command prompt: Enter
deepNetworkDesigner
.
Examples
Related Examples
- Transfer Learning with Deep Network Designer
- Build Networks with Deep Network Designer
- Import Data into Deep Network Designer
- Train Networks Using Deep Network Designer
- Train Network for Time Series Forecasting Using Deep Network Designer
- Train Simple Semantic Segmentation Network in Deep Network Designer
- Image-to-Image Regression in Deep Network Designer
- Transfer Learning with Pretrained Audio Networks in Deep Network Designer
- Import Custom Layer into Deep Network Designer
- Generate MATLAB Code from Deep Network Designer
- 从深Netw导出图像分类网络ork Designer to Simulink
- Generate Experiment Using Deep Network Designer
- View Autogenerated Custom Layers Using Deep Network Designer
- List of Deep Learning Layers
Programmatic Use
Tips
To train multiple networks and compare the results, tryExperiment Manager. You can use Deep Network Designer to create experiments suitable for Experiment Manager.
Version History
Introduced in R2018b