Nlp Interview Notes
📚 专门为自然语言处理(NLP)面试准备的学习笔记与资料
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Ai For Beginners | 30,191 | a month ago | 64 | mit | Jupyter Notebook | |||||
| 12 Weeks, 24 Lessons, AI for All! | ||||||||||
| Text_classification | 7,628 | 7 months ago | 45 | mit | Python | |||||
| all kinds of text classification models and more with deep learning | ||||||||||
| Deeplearning | 7,463 | 2 years ago | 8 | apache-2.0 | Jupyter Notebook | |||||
| 深度学习入门教程, 优秀文章, Deep Learning Tutorial | ||||||||||
| Tensorflow_cookbook | 6,085 | a year ago | 28 | mit | Jupyter Notebook | |||||
| Code for Tensorflow Machine Learning Cookbook | ||||||||||
| Pytorch Sentiment Analysis | 4,133 | 3 months ago | 3 | mit | Jupyter Notebook | |||||
| Tutorials on getting started with PyTorch and TorchText for sentiment analysis. | ||||||||||
| Competition Baseline | 3,773 | 5 months ago | gpl-3.0 | Jupyter Notebook | ||||||
| 数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路 | ||||||||||
| Zhihu | 3,228 | 3 years ago | 31 | Jupyter Notebook | ||||||
| This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code. | ||||||||||
| Awesome Deeplearning | 2,670 | 3 months ago | 462 | apache-2.0 | Jupyter Notebook | |||||
| 深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI | ||||||||||
| Codesearchnet | 2,054 | 2 years ago | 7 | mit | Jupyter Notebook | |||||
| Datasets, tools, and benchmarks for representation learning of code. | ||||||||||
| Practical Machine Learning With Python | 2,054 | a year ago | 19 | apache-2.0 | Jupyter Notebook | |||||
| Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system. | ||||||||||
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