Learn how to use deep learning to identify objects on a live webcam with the AlexNet pretrained network.
This example shows how to classify an image using the pretrained deep convolutional neural network GoogLeNet.
This example shows how to classify images from a webcam in real time using the pretrained deep convolutional neural network GoogLeNet.
This example shows how to use transfer learning to retrain AlexNet, a pretrained convolutional neural network, to classify a new set of images.
Interactively fine-tune a pretrained deep learning network to learn a new image classification task.
This example shows how to create and train a simple convolutional neural network for deep learning classification.
This example shows how to classify sequence data using a long short-term memory (LSTM) network.
Discover deep learning capabilities in MATLAB® using convolutional neural networks for classification and regression, including pretrained networks and transfer learning, and training on GPUs, CPUs, clusters, and clouds.
Learn how to download and use pretrained convolutional neural networks for classification, transfer learning and feature extraction.
An introduction to convolutional neural networks and how they work in MATLAB.
Use apps and functions to design shallow neural networks for function fitting, pattern recognition, clustering, and time series analysis.
Refer to additional sources of information about neural networks.
List of sample data sets to use while experimenting with the toolbox.