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How do autoencoders work, and what are their applications?
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Answer Posted / Vikas Kumar Sharma
Autoencoders are a type of neural network used for learning efficient data codings. They consist of an encoder (an input-to-hidden layer mapping) and a decoder (a hidden-to-output layer mapping). The goal is to learn a representation of the input data that can be reconstructed from the encoded representation.nApplications of autoencoders include anomaly detection, dimensionality reduction, denoising data, and generating new samples. They have been used in various fields such as image processing, speech recognition, and natural language processing.
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