AI Engineering Interpretability Utils
Helper modules for AI Engineering Interpretability Bootcamp implementations.
This package provides reusable utilities for:
- Loading and preprocessing common datasets (Adult, Diabetes, Bank Marketing, Gas Turbine)
- Model training and evaluation helpers
- Visualization utilities for interpretability
Installation
pip install aieng-interp-utils
Usage
from aieng.interp.data import load_adult_dataset, preprocess_adult_data
from aieng.interp.models import train_pytorch_model, get_device
from aieng.interp.visualization import plot_confusion_matrix, plot_roc_curve
# Load and preprocess data
df = load_adult_dataset("path/to/data")
X_train, X_test, y_train, y_test = preprocess_adult_data(df)
# Train model
device = get_device()
model = train_pytorch_model(model, X_train, y_train, device=device)
# Visualize results
plot_roc_curve(y_test, y_pred_proba)
plot_confusion_matrix(y_test, y_pred)
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for aieng-interp-utils 1.0.0
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