Multi-Layer Neural Network Training System
(Redirected from Multi-Layer ANN Training System)
A Multi-Layer Neural Network Training System is a neural-network training system that can apply a deep neural network training algorithm/multi-layer network training algorithm to solve a multi-layer network training task/deep neural network training task (that trains a multi-layer NNet/deep ANN).
- DL4J System.
- Caffe System "Caffe is a deep learning framework developed with cleanliness, readability, and speed in mind. ..."
- Mocha DL System "Mocha is a Deep Learning framework for Julia, inspired by the C++ framework Caffe. ..."
- cuda-covnet "This is a fast C++/CUDA implementation of convolutional (or more generally, feed-forward) neural networks. … "
- GraphLab DeepLearning Create
- a Convolutional Neural Network Training System,
- a Deep Bidirectional Neural Network,
- a Neocognitron Training System,
- an Encoder-Decoder Neural Network Training System.
- a Recurrent Neural Network Training System.
- a Three-Layer Neural Network Training System, ...
- a Deep Belief Network Training System,
- a Perceptron Network Training System, such as:
- a Single Hidden-Layer Neural Network;
- a Single-Layer Feedforward Neural Network.
- See: Deep Neural Network, Multi Hidden-Layer Neural Network.
- (Schmidhuber, 2015) ⇒ Jürgen Schmidhuber. (2015). “Deep Learning in Neural Networks: An Overview.” In: Neural Networks, 61.
- QUOTE: In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning.
- Deeplearning4j, distributed deep learning for the JVM. Parallel GPUs.
- NVIDIA cuDNN library of accelerated primitives for deep neural networks.
- DeepLearnToolbox, Matlab/Octave toolbox for deep learning
- Gensim a toolkit for natural language processing; includes word2vec