Natural Language Processing RoadMap 2019

Data Science, Natural Language Processing

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 textminingratsgo/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

(Nguồn github.com)

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