Deep Learning for NLP 2025
Advanced deep learning techniques for natural language processing with modern architectures and Korean language applications
- Documentation: https://deepnlp2025.jeju.ai
- GitHub: https://github.com/entelecheia/deepnlp-2025
- PyPI: https://pypi.org/project/deepnlp-2025
This course focuses on advanced deep learning techniques for natural language processing, covering state-of-the-art architectures including Transformers, State Space Models (Mamba, RWKV), and parameter-efficient fine-tuning methods. Students will learn prompt engineering, RAG systems, RLHF alternatives, and build practical NLP applications with Korean language datasets.
Changelog
See the CHANGELOG for more information.
Contributing
Contributions are welcome! Please see the contributing guidelines for more information.
License
This project is released under the CC-BY-4.0 License.
1 maintainer
Metadata
1 maintainer
Release files for deepnlp-2025 0.2.0
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| deepnlp_2025-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.2 MB
Release files / deepnlp_2025-0.2.0.tar.gz
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