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Summary:
Implementing easy-to-use methods for classical and novel tabular data augmentation and synthesis.
Latest version:
0.0.18
Required dependencies:
catboost
|
category-encoders
|
ctgan
|
ema-pytorch
|
icecream
|
imbalanced-learn
|
libzero
|
optuna
|
rtdl
|
scikit-learn
|
sdv
|
tensorboard
|
tomli
|
tomli-w
|
torchvision
|
tqdm
|
xgboost
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