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3 results for “neural-network”
Foundations
Autoencoder
An autoencoder is a type of artificial neural network trained to reconstruct its input through a compressed internal representation, used for dimensionality reduction, feature learning, and anomaly detection.
5 min readUpdated May 2026
Foundations
Encoder-Decoder Architecture
A neural network design pattern that compresses an input sequence into an internal representation using an encoder, and then generates an output sequence from that representation using a decoder, foundational to machine translation, summarisation, and many other sequence-to-sequence tasks.
6 min readUpdated May 2026
Foundations
Long Short-Term Memory (LSTM)
Long Short-Term Memory is a recurrent neural network architecture designed to learn long-range dependencies in sequential data by using gating mechanisms to control information flow.
5 min readUpdated May 2026