An autoencoder is deep learning’s solution to dimensionality reduction problems. The idea is plain & simple: transform the input vectors through a series of hidden layers and maintain the final output layer with the same dimension as the input layer. However, the intermediate hidden layers have smaller number of neurons (and therefore, helps in reducing the dimensions … Continue reading Telecom Churn modelling- variational autoencoders
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