Deep Learning Toolbox

Design, train, analyze, and simulate deep learning networks

Deep Learning Toolbox™ provides functions, apps, and Simulink® blocks for designing, implementing, and simulating deep neural networks. The toolbox provides a framework to create and use many types of networks, such as convolutional neural networks (CNNs) and transformers. You can visualize and interpret network predictions, verify network properties, and compress networks with quantization, projection, or pruning.

With the Deep Network Designer app, you can design, edit, and analyze networks interactively, import pretrained models, and export networks to Simulink. The toolbox lets you interoperate with other deep learning frameworks. You can import PyTorch®, TensorFlow™, and ONNX™ models for inference, transfer learning, simulation, and deployment. You can also export models to TensorFlow and ONNX.

You can automatically generate C/C++, CUDA® and HDL code for trained networks.

Get Started

Learn the basics of Deep Learning Toolbox

Applications

Explore deep learning workflows with computer vision, image processing, automated driving, signals, audio, text analytics, and computational finance

Deep Learning with Simulink

Extend deep learning workflows using Simulink

Preprocess Data for Deep Neural Networks

Manage and preprocess data for deep learning

Import and Build Deep Neural Networks

Build networks using command-line functions or interactively using the Deep Network Designer app

Train Deep Neural Networks

Train networks using built-in training functions or custom training loops

Visualize and Verify Deep Neural Networks

Visualize network behavior, explain predictions, and verify robustness

Generate Code and Deploy Deep Neural Networks

Generate C/C++, CUDA, or HDL code and export or deploy deep learning networks