DeepCoreML 0.2.2

A collection of Machine Learning techniques for data management and augmentation.

DeepCoreML is a collection of Machine Learning techniques for data management, engineering, and augmentation. More specifically, DeepCoreML includes modules for:

• Dataset management
• Text data preprocessing
• Text representation, vectorization, embeddings
• Dimensionality Reduction
• Generative Modeling
• Imbalanced Datasets

Licence:

Apache License, 2.0 (Apache-2.0)

Dependencies: scikit-learn, imbalanced-learn, pytorch, numpy, pandas.

GitHub repository: https://github.com/lakritidis/DeepCoreML

Publications:

• 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.
• 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.
• L. Akritidis, P. Bozanis, "Low Dimensional Text Representations for Sentiment Analysis NLP Tasks", Springer Nature (SN) Computer Science, vol. 4, no. 5, 474, 2023.