Module utils 

Utility functions for neural networks

This module provides various utility functions for neural networks, such as weight initialization strategies, metric calculations, positional encoding for transformer models, etc.

Re-exports

pub use colors::color_legend;

pub use colors::colored_metric_cell;

pub use colors::colorize;

pub use colors::colorize_and_style;

pub use colors::colorize_bg;

pub use colors::gradient_color;

pub use colors::stylize;

pub use colors::Color;

pub use colors::ColorOptions;

pub use colors::Style;

pub use evaluation::ConfusionMatrix;

pub use evaluation::FeatureImportance;

pub use evaluation::LearningCurve;

pub use evaluation::ROCCurve;

pub use model_viz::sequential_model_dataflow;

pub use model_viz::sequential_model_summary;

pub use model_viz::ModelVizOptions;

pub use initializers::*;

pub use metrics::*;

Modules

colors

Terminal color utilities for visualization Terminal color utilities for visualization output

datasets

Placeholder for datasets module

evaluation

Evaluation utilities and visualizations for model performance Evaluation utilities and visualizations for model performance

initializers

Weight initialization strategies for neural networks

metrics

Evaluation metrics for neural networks

model_viz

Model architecture visualization utilities Model architecture visualization utilities

Functions

one_hot_encode

Calculate the one-hot encoding of a vector of indices

random_normal

Generate a random vector or matrix with values from a normal distribution

train_test_split

This function splits input and target data into training and testing sets.

Type Aliases

TrainTestSplitResult

Split data into training and testing sets