Autoencoders are a type of artificial neural network used for unsupervised learning. They are designed to learn efficient codings of unlabeled data, typically for the purpose of dimensionality reduction.

• Anomaly Detection
• Image Noise Reduction
• Feature Learning/Extraction
• Text Analysis
• Data Compression
• Image Generation
• Data Decoding

An example of an autoencoder is a neural network that takes a picture as input and learns to compress it into a lower-dimensional representation while preserving the most important features. This compressed representation can then be used for tasks such as image recognition or classification.

• Current state of data in your organization