semvec/pypi-packages huggingface dataset:
DeepCoreML 0.4.14
A collection of Machine Learning techniques for data management, engineering and augmentation.
License: Apache
Keywords: tabular data, tabular data synthesis, data engineering, imbalanced data, GAN, VAE, oversampling, machine learning, deep learning

<p>DeepCoreML is a collection of Machine Learning techniques for data management, engineering, and augmentation. More specifically, DeepCoreML includes modules for:</p><ul><li>Data management</li><li>Text data preprocessing</li><li>Text representation, vectorization, embeddings</li><li>Dimensionality reduction</li><li>Generative modeling</li><li>Imbalanced datasets</li></ul><p><b>Licence:</b> Apache License, 2.0 (Apache-2.0)</p><p><b>Dependencies:</b>NumPy, Pandas, Matplotlib, Seaborn, joblib, Synthetic Data Vault (SDV), pyTorch,scikit-learn, xgboost, imblearn, Reversible Data Transforms (RDT), tqdm.</p><p><b>GitHub repository:</b> <a href="https://github.com/lakritidis/DeepCoreML">https://github.com/lakritidis/DeepCoreML</a></p><p><b>Publications:</b><ul><li>L. Akritidis, P. Bozanis, "A Clustering-Based Resampling Technique with Cluster Structure Analysis forSoftware Defect Detection in Imbalanced Datasets", Information Sciences, vol. 674, pp. 120724, 2024.</li><li>L. Akritidis, A. Fevgas, M. Alamaniotis, P. Bozanis, "Conditional Data Synthesis with Deep Generative Models for Imbalanced Dataset Oversampling", In Proceedings of the 35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pp. 444-451, 2023, 2023.</li></ul></p>