DeepLearnToolbox is a MATLAB / Octave toolbox for prototyping deep learning models. It provides implementations of feedforward neural networks, convolutional neural networks (CNNs), deep belief networks (DBNs), stacked autoencoders, convolutional autoencoders, and more. The toolbox includes example scripts for each method, enabling users to quickly experiment with architectures, training, and inference workflows. Although it's been flagged as deprecated and no longer actively maintained, it is still used for educational and prototyping purposes. Deep belief networks (DBN) and restricted Boltzmann machines (RBM). Example scripts demonstrating usage.
Features
- Implementation of multilayer perceptrons with backpropagation
- Convolutional neural networks (CNN) modules
- Deep belief networks (DBN) and restricted Boltzmann machines (RBM)
- Stacked autoencoder and convolutional autoencoder support
- Utility / helper functions for training, data loading, activation, cost, gradient
- Example scripts demonstrating usage