DeepLearnToolbox
A MATLAB/Octave toolbox for deep learning with implementations of neural networks, deep belief nets, autoencoders, and convolutional networks.
What is DeepLearnToolbox?
DeepLearnToolbox is a MATLAB/Octave toolbox that implements several deep learning algorithms including Deep Belief Networks, Stacked Autoencoders, Convolutional Neural Networks, and standard neural networks. It provides researchers and students with working implementations to learn about and experiment with deep hierarchical models of data in a familiar scientific computing environment.
Researchers, students, and practitioners who want to learn about deep learning algorithms using MATLAB or Octave, particularly those in academic settings who prefer these scientific computing environments over Python-based frameworks.
It offers clean, educational implementations of fundamental deep learning algorithms with working examples, making it easier to understand the underlying concepts without the complexity of modern deep learning frameworks. The toolbox is specifically designed for MATLAB/Octave users who want to experiment with deep learning in their preferred environment.
Overview
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
Use Cases
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