Mini toolsDefinition
Neural networks that learn to compress data into a lower-dimensional representation and then reconstruct it
Detailed Explanation
Autoencoders consist of an encoder that compresses input data into a latent representation and a decoder that reconstructs the original input from this representation. They are trained to minimize reconstruction error while learning efficient data representations.
Use Cases
Dimensionality reduction, feature learning, anomaly detection, image compression
