ML-NLP
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
Study key concepts and coding examples for machine learning and natural language processing interviews.
From the README
- 此项目是机器学习、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
- 既然是以面试为主要目的，亦不可以篇概全，请谅解，有问题可提出。
- 此项目以各个模块为切入点，让大家有一个清晰的知识体系。
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
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Free · no card · unsubscribe anytime此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
ML-NLP has 17.8k stars on GitHub. It has been forked 4.6k times. ML-NLP is written mainly in Jupyter Notebook. It has been in active development since 2019. Its main topics are deep-learning, machine-learning, nlp.
What is ML-NLP?
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
Is ML-NLP open source?
ML-NLP is an open-source project.
Is ML-NLP free?
Yes. ML-NLP is free and open source — you can use, modify and self-host it.
What language is ML-NLP written in?
ML-NLP is written mainly in Jupyter Notebook.
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