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.
- 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.
Probability & Statistics
Natural Language Processing
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.
 Christopher Bishop(2006). Pattern Recognition and Machine Learning
 Young, T., Hazarika, D., Poria, S., & Cambria, E. (2017). Recent Trends in Deep Learning Based Natural Language Processing. arXiv preprint arXiv:1708.02709.
The class is licensed under the MIT License:
Copyright © 2019 Tae-Hwan Jung.