Awesome

nlp-roadmap

nlp-roadmap is Natural Language Processing ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning Natural Language Processing. The roadmap covers the materials from basic probability/statistics to SOTA NLP models.

Caution!

• The relationship among keywords could be interpreted in ambiguous ways since they are represented in the format of a semantic mind-map. Please just focus on KEYWORD in square box, and deem them as the essential parts to learn.
• The work of containing a plethora of keywords and knowledge within just an image has been challenging. Thus, please note that this roadmap is one of the suggestions or ideas.
• You are eligible for using the material of your own free will including commercial purpose but highly expected to leave a reference.

Curriculum

1. Probability and Statistics

2. Machine Learning

3. Text Mining

4. Natural Language Processing

Probability & Statistics

Machine Learning

Text Mining

Natural Language Processing

Contribution

Everyone can contribute to the repository. Contributions can range fixing typos to giving different perspectives on the materials. I welcome your contribution under the identical contribution guide of kamranahmedse/developer-roadmap.

Reference

[1] ratsgo's blog for textmining, ratsgo/ratsgo.github.io

[2] (한국어) 텍스트 마이닝을 위한 공부거리들, lovit/textmining-tutorial

[3] Christopher Bishop(2006). Pattern Recognition and Machine Learning

[4] Young, T., Hazarika, D., Poria, S., & Cambria, E. (2017). Recent Trends in Deep Learning Based Natural Language Processing. arXiv preprint arXiv:1708.02709.

[5] curated collection of papers for the nlp practitioner, mihail911/nlp-library

Acknowledgement to ratsgo, lovit for creating great posts and lectures.

LICENSE

The class is licensed under the MIT License:

Copyright © 2019 Tae-Hwan Jung.

Author

• Tae Hwan Jung @graykode, Kyung Hee Univ CE(Undergraduate).
• Author Email : nlkey2022@gmail.com