Expand description
Autoencoder implementation for unsupervised feature learning
This module provides various autoencoder architectures including:
- Standard autoencoder for dimensionality reduction
- Denoising autoencoder for data cleaning
- Sparse autoencoder for feature learning
- Deep autoencoder for complex representations
Structs§
- Autoencoder
- Simple Autoencoder model
- Autoencoder
Config - Autoencoder configuration
Enums§
- Optimizer
Type - Optimizer types for training