Autoencounter in Machine Learning
DOI:
https://doi.org/10.61173/p7hxhp58Keywords:
Autoencoders, Dimensionality Reduction, Feature Extraction, Unsupervised Learning, Generative Models, Anomaly Detection, Image DenoisingAbstract
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.
