AiLearning-Theory-Applying
快速上手AI理论及应用实战：基础知识、Transformer、NLP、ML、DL、竞赛。含大量注释及数据集，力求每一位能看懂并复现。
Learn AI concepts and apply them through practical examples with annotated datasets and clear explanations.
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AiLearning-Theory-Applying has 3.5k stars on GitHub. It has been forked 483 times. AiLearning-Theory-Applying is written mainly in Jupyter Notebook. It has been in active development since 2020. AiLearning-Theory-Applying is available under the MIT license. Its main topics are ai, bert, dataming, deep-learning.
What is AiLearning-Theory-Applying?
快速上手AI理论及应用实战：基础知识、Transformer、NLP、ML、DL、竞赛。含大量注释及数据集，力求每一位能看懂并复现。
Is AiLearning-Theory-Applying open source?
AiLearning-Theory-Applying is an open-source project. It is released under the MIT license.
Is AiLearning-Theory-Applying free?
Yes. AiLearning-Theory-Applying is free and open source — you can use, modify and self-host it.
What license does AiLearning-Theory-Applying use?
AiLearning-Theory-Applying is available under the MIT license.
What language is AiLearning-Theory-Applying written in?
AiLearning-Theory-Applying is written mainly in Jupyter Notebook.
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