看到Reddit和Github上一个有意思的项目：graykode/nlp-roadmap

ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning NLP

Github链接：https://github.com/graykode/nlp-roadmap

graykode/nlp-roadmapgithub.com

主要总结了NLP相关的路线图（思维导图）和关键词（知识点），包括概率和统计、机器学习、文本挖掘、自然语言处理几个部分。以下是作者在Reddit上的介绍文章：

https://www.reddit.com/r/MachineLearning/comments/d8jheo/p_natural_language_processing_roadmap_and_keyword/www.reddit.com

Natural Language Processing Roadmap and Keyword for students who are wondering what to study

I created summarized Natural Language Processing Roadmap in Github Repository with preparing NLP Engineer Interview to not forgetting which i had learned things. :D :D

It's contain in order Probability and Statistics, Machine Learning, Text Mining, Natural Language Processing.

It was very hard to make tree, sub-tree sctucture of mind map with abstract keywords, so Please focus on KEYWORD in square box, as things to study.

Also You can use the material commercially or freely, but please leave the source.

If you like the project, please ask star, fork and Contribution! :D Thanks!!

以下文字图片来自该项目github，感兴趣的同学可以关注：github.com/graykode/nlp

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

Opens for everybody to contribute to the repository, including typo or 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

点击阅读原文可直达该项目Github链接，推荐Star。