Build networks from scratch using MATLAB ® code or interactively using the Deep Network Designer app. Use built-in layers to construct networks for tasks such as classification and regression. To see a list of built-in layers, see List of Deep Learning Layers. You can then analyze your network to understand the network architecture and check for problems before training.
If the built-in layers do not provide the layer that you need for your task, then you can define your own custom deep learning layer. You can define custom layers with learnable and state parameters. After you define a custom layer, you can check that the layer is valid, GPU compatible, and outputs correctly defined gradients.
For models that cannot be specified as networks of layers, you can define the model as a function. For an example showing how to train a deep learning model defined as a function, see Train Network Using Model Function.
| Deep Network Designer | Design and visualize deep learning networks |