Neural Network Toolbox™ provides algorithms, pretrained models, and apps to create, train, visualize, and simulate both shallow and deep neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control.
Deep learning networks include convolutional neural networks (ConvNets, CNNs) and autoencoders for image classification, regression, and feature learning.
For small training sets, you can quickly apply deep learning by performing transfer learning with pretrained deep networks. To speed up training on large data sets, you can use Parallel Computing Toolbox™ to distribute computations and data across multicore processors and GPUs on the desktop, and you can scale up to clusters and clouds (including Amazon EC2® P2 GPU instances) with MATLAB Distributed Computing Server™.
Improve the efficiency of neural network training.Learn more
Discover more about Neural Network Toolbox by exploring these resources.
Explore documentation for Neural Network Toolbox functions and features, including release notes and examples.
Browse the list of available Neural Network Toolbox functions.
View system requirements for the latest release of Neural Network Toolbox.
View articles that demonstrate technical advantages of using Neural Network Toolbox.
Neural Network Toolbox requires: MATLAB
Use Neural Network Toolbox to solve scientific and engineering challenges: