Welcome to nn-toolbox’s documentation!¶

`nntoolbox.callbacks`	Implementations of training procedures
`nntoolbox.components`	General components for neural networks
`nntoolbox.ensembler`	Methods for generating an ensemble of models
`nntoolbox.hooks`	Abstraction for pytorch hooks (similar to callbacks but for layers)
`nntoolbox.init`	Initializers for weight layers
`nntoolbox.losses`	Some generic loss functions
`nntoolbox.metrics`	Metrics for model evaluation
`nntoolbox.models`	Abstraction for machine learning modelling (e.g classifier, ensemble, etc.)
`nntoolbox.optim`	Optimizers and optimization utility functions
`nntoolbox.sequence`	Components, learners, losses, models, transformations and utility functions for sequence tasks.
`nntoolbox.tabular`	For tabular data and recommendation systems
`nntoolbox.transforms`	Some generic data transformations
`nntoolbox.utils`	Some generic utilities function for neural networks
`nntoolbox.vision`	Components, learners, losses, models, transformations and utility functions for vision tasks.
`nntoolbox.visualization`	Utilities for model and data visualization

Indices and tables¶