What is an autoencoder in machine learning?
Experience Level: Junior
Tags: Machine learning
Answer
An autoencoder is a type of neural network that is designed to learn a compressed representation of the input data, typically for the purpose of dimensionality reduction or feature extraction. It consists of an encoder network that maps the input data to a lower-dimensional latent representation, and a decoder network that maps the latent representation back to the original input space. Autoencoders can be trained using unsupervised learning and have been successfully applied in a wide range of applications, such as image compression, anomaly detection, and natural language processing.
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