Implementation of the stacked denoising autoencoder in Tensorflow
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Updated
Aug 21, 2018 - Python
Implementation of the stacked denoising autoencoder in Tensorflow
用Tensorflow实现的深度神经网络。
implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)
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Collection of autoencoder models in Tensorflow
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A repository for compiling unsupervised learning implementations in tensorflow
We use stacked Autoencoders to build a powerfull recommender system for movies.
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An autoencoder is a type of artificial neural network used for unsupervised learning of efficient data codings. The aim of an autoencoder is to learn a representation (encoding) for a set of data, typically for dimensionality reduction, feature learning, or data denoising, without supervision.
Um modelo de redes autoassociativas empilhadas para detectar faltas em transformadores de potência
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