Metadata-Version: 2.1
Name: DeepCoreML
Version: 0.3.2
Summary: A collection of Machine Learning techniques for data management, engineering and augmentation.
Home-page: https://github.com/lakritidis/DeepCoreML
Author: Leonidas Akritidis
Author-email: lakritidis@ihu.gr
Maintainer: Leonidas Akritidis
Maintainer-email: lakritidis@ihu.gr
License: Apache
Keywords: data engineering,data management,text vectorization,text processing,dimensionality reduction,imbalanced data,machine learning,deep learning
Platform: UNKNOWN
Description-Content-Type: text/markdown
License-File: LICENSE

<p>DeepCoreML is a collection of Machine Learning techniques for data management, engineering, and augmentation. More specifically, DeepCoreML includes modules for:</p><ul><li>Dataset 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> scikit-learn, imblearn, pytorch, numpy, pandas, transformers, nltk, matplotlib</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, 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), to appear, 2023.</li><li>L. Akritidis, P. Bozanis, "A Multi-Dimensional Survey on Learning from Imbalanced Data", Chapter in Machine Learning Paradigms - Advances in Theory and Applications of Learning from Imbalanced Data, to appear, 2023.</li><li>L. Akritidis, P. Bozanis, "<a href="https://link.springer.com/article/10.1007/s42979-023-01913-y">Low Dimensional Text Representations for Sentiment Analysis NLP Tasks</a>", Springer Nature (SN) Computer Science, vol. 4, no. 5, 474, 2023.</li></ul></p>

