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SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. It is designed with an intuitive programming model based on the layer abstraction. A variety of popular deep learning models are supported, namely feed-forward models including ... [More] convolutional neural networks (CNN), energy models like restricted Boltzmann machine (RBM), and recurrent neural networks (RNN). Many built-in layers are provided for users. SINGA architecture is sufficiently flexible to run synchronous, asynchronous and hybrid training frameworks. SINGA also supports different neural net partitioning schemes to parallelize the training of large models, namely partitioning on batch dimension, feature dimension or hybrid partitioning. [Less]

zeta-learn is a minimalistic python machine learning library designed to deliver fast and easy model prototyping. zeta-learn aims to provide an extensive understanding of machine learning through the use of straightforward algorithms and readily implemented examples making it a useful resource for researchers and students.

RNNoise is a noise suppression library based on a recurrent neural network.