Autoencounter in Machine Learning
Wenen Yang · Science and Technology of Engineering Chemistry and Environmental Protection · 2024
An Autoencoder is a type of neural network model that learns compressed, encoded representations of data, usually for dimensionality reduction or feature extraction. Despite its apparent simplicity, autoencoder serves a vital role in machine learning, particularly in applications that need unsupervised learning.