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Deep Learning

Construct and train convolutional neural networks (CNNs, ConvNets) for classification and regression and autoencoder neural networks for learning features

Deep learning uses neural networks to learn useful representations of features directly from data. If you have labeled data, perform supervised learning with convolutional neural networks (CNNs, ConvNets) for classification, regression, and transfer learning using pretrained networks. If you have unlabeled data, perform unsupervised learning with autoencoder neural networks for feature extraction. To get started, see Deep Learning in MATLAB.

  • Convolutional Neural Networks
    Perform classification, regression, feature extraction, and transfer learning using convolutional neural networks (CNNs, ConvNets)
  • Autoencoders
    Perform unsupervised learning of features using autoencoder neural networks

Featured Examples

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