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<a href="https://github.com/GrowingGit/GitHub-Chinese-Top-Charts#github中文排行榜">返回目录</a> • <a href="/content/docs/feedback.md">问题反馈</a>
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# 中文增速榜 > 资料类 > Jupyter Notebook
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<sub>数据更新: 2024-03-18 / 温馨提示：中文项目泛指「文档母语为中文」OR「含有中文翻译」的项目，通常在项目的「readme/wiki/官网」可以找到</sub>
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|#|Repository|Description|Stars|Average daily growth|Updated|
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|1|[datawhalechina/prompt-engineering-for-developers](https://github.com/datawhalechina/prompt-engineering-for-developers)|面向开发者的 LLM 入门教程，吴恩达大模型系列课程中文版|8483|26|2024-03-17|
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|2|[fastai/fastbook](https://github.com/fastai/fastbook)|The fastai book, published as Jupyter Notebooks|20469|14|2024-03-17|
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|3|[williamyang1991/Rerender_A_Video](https://github.com/williamyang1991/Rerender_A_Video)|[SIGGRAPH Asia 2023] Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation|2850|9|2024-03-09|
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|4|[selfteaching/the-craft-of-selfteaching](https://github.com/selfteaching/the-craft-of-selfteaching)|One has no future if one couldn't teach themself.|14922|8|2024-01-31|
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|5|[datawhalechina/self-llm](https://github.com/datawhalechina/self-llm)|《开源大模型食用指南》基于AutoDL快速部署开源大模型，更适合中国宝宝的部署教程|981|8|2024-03-17|
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|6|[datawhalechina/llm-universe](https://github.com/datawhalechina/llm-universe)|本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/|961|7|2024-03-17|
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|7|[huggingface/diffusion-models-class](https://github.com/huggingface/diffusion-models-class)|Materials for the Hugging Face Diffusion Models Course|3120|6|2023-12-18|
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|8|[datawhalechina/easy-rl](https://github.com/datawhalechina/easy-rl)|强化学习中文教程（蘑菇书），在线阅读地址：https://datawhalechina.github.io/easy-rl/|7915|6|2024-03-09|
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|9|[Visualize-ML/Book1_Python-For-Beginners](https://github.com/Visualize-ML/Book1_Python-For-Beginners)|Book_1_《编程不难》 鸢尾花书：从加减乘除到机器学习；请多多批评指正！|3047|6|2024-03-16|
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|10|[solidglue/Deep_Learning_TensorFlow2_Examples](https://github.com/solidglue/Deep_Learning_TensorFlow2_Examples)|Deep Learning TensorFlow2 API and Examples with Python3 and Jupyter Notebook.|92|5|2024-03-01|
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|11|[AccumulateMore/CV](https://github.com/AccumulateMore/CV)|✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】|3404|5|2024-03-17|
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|12|[solidglue/Machine_Learning_Sklearn_Examples](https://github.com/solidglue/Machine_Learning_Sklearn_Examples)|机器学习Sklearn入门指南。Machine Learning Sklearn API and Examples with Python3 and Jupyter Notebook.|100|5|2024-03-14|
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|13|[chenyuntc/pytorch-book](https://github.com/chenyuntc/pytorch-book)|PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)|11617|5|2023-12-24|
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|14|[wesm/pydata-book](https://github.com/wesm/pydata-book)|Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media|21117|5|2023-12-22|
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|15|[huggingface/cookbook](https://github.com/huggingface/cookbook)|Open-source AI cookbook|471|4|2024-03-15|
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|16|[apachecn/Interview](https://github.com/apachecn/Interview)|Interview = 简历指南 + 算法题 + 八股文 + 源码分析|8467|4|2023-10-20|
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|17|[Visualize-ML/Book5_Essentials-of-Probability-and-Statistics](https://github.com/Visualize-ML/Book5_Essentials-of-Probability-and-Statistics)|Book_5_《统计至简》 鸢尾花书：从加减乘除到机器学习；上架！|2144|4|2024-03-16|
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|18|[Visualize-ML/Book2_Beauty-of-Data-Visualization](https://github.com/Visualize-ML/Book2_Beauty-of-Data-Visualization)|Book_2_《可视之美》 鸢尾花书：从加减乘除到机器学习，欢迎批评指正|1939|4|2024-03-16|
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|19|[zyds/transformers-code](https://github.com/zyds/transformers-code)|手把手带你实战 Huggingface Transformers 课程视频同步更新在B站与YouTube|920|3|2024-03-03|
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|20|[Visualize-ML/Book7_Visualizations-for-Machine-Learning](https://github.com/Visualize-ML/Book7_Visualizations-for-Machine-Learning)|Book_7_《机器学习》 鸢尾花书：从加减乘除到机器学习；欢迎批评指正|1693|3|2024-03-16|
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|21|[EgoAlpha/prompt-in-context-learning](https://github.com/EgoAlpha/prompt-in-context-learning)|Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.|1297|3|2024-03-16|
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|22|[datawhalechina/joyful-pandas](https://github.com/datawhalechina/joyful-pandas)|pandas中文教程|4258|3|2023-10-16|
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|23|[unit-mesh/unit-minions](https://github.com/unit-mesh/unit-minions)|《AI 研发提效研究：自己动手训练 LoRA》，包含 Llama （Alpaca LoRA）模型、ChatGLM （ChatGLM Tuning）相关 Lora 的训练。训练内容：用户故事生成、测试代码生成、代码辅助生成、文本转 SQL、文本生成代码……|963|3|2024-01-03|
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|24|[charent/Phi2-mini-Chinese](https://github.com/charent/Phi2-mini-Chinese)|Phi2-Chinese-0.2B 从0开始训练自己的Phi2中文小模型，支持接入langchain加载本地知识库做检索增强生成RAG。Training your own Phi2 small chat model from scratch.|269|3|2024-02-19|
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|25|[TradeMaster-NTU/TradeMaster](https://github.com/TradeMaster-NTU/TradeMaster)|TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:|1021|2|2024-02-28|
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|26|[datawhalechina/thorough-pytorch](https://github.com/datawhalechina/thorough-pytorch)|PyTorch入门教程，在线阅读地址：https://datawhalechina.github.io/thorough-pytorch/|1862|2|2024-03-17|
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|27|[gedeck/practical-statistics-for-data-scientists](https://github.com/gedeck/practical-statistics-for-data-scientists)|Code repository for O'Reilly book|2406|2|2024-02-12|
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|28|[WTFAcademy/WTF-zk](https://github.com/WTFAcademy/WTF-zk)|零知识证明入门教程。|274|2|2024-03-16|
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|29|[xuwenhao/geektime-ai-course](https://github.com/xuwenhao/geektime-ai-course)|Jupyter Notebooks for Geektime AI Course|660|2|2024-02-13|
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|30|[openvinotoolkit/openvino_notebooks](https://github.com/openvinotoolkit/openvino_notebooks)|📚 Jupyter notebook tutorials for OpenVINO™|1858|2|2024-03-15|
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|31|[MLEveryday/practicalAI-cn](https://github.com/MLEveryday/practicalAI-cn)|AI实战-practicalAI 中文版|3191|2|2023-12-31|
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|32|[PaddlePaddle/awesome-DeepLearning](https://github.com/PaddlePaddle/awesome-DeepLearning)|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|2743|2|2024-03-07|
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|33|[DjangoPeng/LLM-quickstart](https://github.com/DjangoPeng/LLM-quickstart)|Quick Start for Large Language Models (Theoretical Learning and Practical Fine-tuning) 大语言模型快速入门（理论学习与微调实战）|196|2|2024-03-13|
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|34|[ben1234560/AiLearning-Theory-Applying](https://github.com/ben1234560/AiLearning-Theory-Applying)|快速上手Ai理论及应用实战：基础知识、ML、DL、NLP-BERT、竞赛。含大量注释及数据集，力求每一位能看懂并复现。|2818|2|2024-02-19|
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|35|[fengdu78/WZU-machine-learning-course](https://github.com/fengdu78/WZU-machine-learning-course)|温州大学《机器学习》课程资料（代码、课件等）|1652|2|2023-11-19|
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|36|[WTFAcademy/WTF-EVM-Opcodes](https://github.com/WTFAcademy/WTF-EVM-Opcodes)|Minimal tutorials for EVM Opcodes, building minimal evm in python from scratch. 以太坊的Opcodes（操作码）极简教程，使用python从零搭建EVM。|125|1|2023-12-31|
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|37|[datawhalechina/team-learning-program](https://github.com/datawhalechina/team-learning-program)|主要存储Datawhale组队学习中“编程、数据结构与算法”方向的资料。|795|1|2023-11-17|
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|38|[yunwei37/Prompt-Engineering-Guide-zh-CN](https://github.com/yunwei37/Prompt-Engineering-Guide-zh-CN)|🐙 关于提示词工程（prompt）的指南、论文、讲座、笔记本和资源大全（自动持续更新）|304|1|2023-10-25|
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|39|[jm199504/Financial-Knowledge-Graphs](https://github.com/jm199504/Financial-Knowledge-Graphs)|小型金融知识图谱构建流程|2519|1|2023-11-02|
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|40|[SMILELab-FL/FedLab](https://github.com/SMILELab-FL/FedLab)|A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.|633|1|2024-01-31|
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|41|[xinychen/latex-cookbook](https://github.com/xinychen/latex-cookbook)|LaTeX论文写作教程 (清华大学出版社)|1217|1|2023-11-21|
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|42|[XingYu-Zhong/LangChainStudy](https://github.com/XingYu-Zhong/LangChainStudy)|这个项目是一个Jupyter notebook的集合，专门用于学习和探索LangChain框架。|142|1|2024-01-16|
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|43|[zlotus/notes-linear-algebra](https://github.com/zlotus/notes-linear-algebra)|线性代数笔记|3294|1|2023-09-17|
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|44|[princepride/scratch-pytorch-step-by-step](https://github.com/princepride/scratch-pytorch-step-by-step)|教你只用最基本的python语法和numpy一步步实现深度学习框架|106|1|2024-03-15|
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|45|[amaargiru/pycore](https://github.com/amaargiru/pycore)|Python Extended Cheatsheet. I'm using this repository to chronicle my journey through Python.|486|1|2024-03-07|
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|46|[KMnO4-zx/huanhuan-chat](https://github.com/KMnO4-zx/huanhuan-chat)|Chat-甄嬛是利用《甄嬛传》剧本中所有关于甄嬛的台词和语句，基于ChatGLM2进行LoRA微调得到的模仿甄嬛语气的聊天语言模型。|258|1|2023-11-18|
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|47|[luwill/Machine_Learning_Code_Implementation](https://github.com/luwill/Machine_Learning_Code_Implementation)|Mathematical derivation and pure Python code implementation of machine learning algorithms.|1480|1|2024-02-01|
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|48|[L1aoXingyu/code-of-learn-deep-learning-with-pytorch](https://github.com/L1aoXingyu/code-of-learn-deep-learning-with-pytorch)|This is code of book "Learn Deep Learning with PyTorch"|2709|1|2024-03-04|
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|49|[ga642381/ML2021-Spring](https://github.com/ga642381/ML2021-Spring)|**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2021 Spring|746|1|2023-11-09|
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|50|[AccumulateMore/OpenCV](https://github.com/AccumulateMore/OpenCV)|✔（已完结）最全面的 OpenCV 笔记【咕泡唐宇迪】|416|1|2023-09-27|
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|51|[CNFeffery/DataScienceStudyNotes](https://github.com/CNFeffery/DataScienceStudyNotes)|这个仓库保管从（数据科学学习手札69）开始的所有代码、数据等相关附件内容|1165|1|2024-02-03|
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|52|[pariskang/CMLM-ZhongJing](https://github.com/pariskang/CMLM-ZhongJing)|首个中医大语言模型——“仲景”。受古代中医学巨匠张仲景深邃智慧启迪，专为传统中医领域打造的预训练大语言模型。 The first-ever Traditional Chinese Medicine large language model - "CMLM-ZhongJing". Inspired by the profound wisdom of the ancient Chinese medi ...|161|1|2024-02-24|
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|53|[datawhalechina/statistical-learning-method-solutions-manual](https://github.com/datawhalechina/statistical-learning-method-solutions-manual)|统计学习方法习题解答，在线阅读地址：https://datawhalechina.github.io/statistical-learning-method-solutions-manual|1540|1|2024-02-06|
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|54|[szcf-weiya/ESL-CN](https://github.com/szcf-weiya/ESL-CN)|The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。|2327|1|2023-11-30|
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|55|[datawhalechina/machine-learning-toy-code](https://github.com/datawhalechina/machine-learning-toy-code)|《机器学习》（西瓜书）代码实战|510|1|2024-02-23|
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|56|[OML-Team/open-metric-learning](https://github.com/OML-Team/open-metric-learning)|Library for metric learning pipelines and models.|745|1|2024-02-21|
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|57|[windmaple/Gemma-Chinese-instruction-tuning](https://github.com/windmaple/Gemma-Chinese-instruction-tuning)|演示Gemma中文指令微调的教程|25|1|2024-02-26|
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|58|[datawhalechina/d2l-ai-solutions-manual](https://github.com/datawhalechina/d2l-ai-solutions-manual)|《动手学深度学习》习题解答，在线阅读地址如下：|232|1|2024-03-10|
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|59|[datawhalechina/hands-on-data-analysis](https://github.com/datawhalechina/hands-on-data-analysis)|动手学数据分析以项目为主线，知识点孕育其中，通过边学、边做、边引导来得到更好的学习效果|1022|1|2024-03-06|
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|60|[ArronAI007/Awesome-AGI](https://github.com/ArronAI007/Awesome-AGI)|AGI资料汇总学习（主要包括LLM和AIGC），持续更新......|108|1|2024-03-16|
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|61|[datawhalechina/wow-plotly](https://github.com/datawhalechina/wow-plotly)|高级可视化神器plotly的学习|47|0|2024-01-12|
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|62|[buluslee/DT-AI](https://github.com/buluslee/DT-AI)|这是DT-AI的学习路线开源版本，欢迎大家享用！对新手友好|96|0|2024-01-29|
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|63|[zzy99/My-competition-solutions](https://github.com/zzy99/My-competition-solutions)|我的数据竞赛方案总结|63|0|2023-11-18|
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|64|[fry404006308/fry_course_materials](https://github.com/fry404006308/fry_course_materials)|范仁义录播课资料，会依次推出各种完全免费的前端、后端、大数据、人工智能等课程，课程网站： https://fanrenyi.com ； b站课程地址： https://space.bilibili.com/45664489 ；|498|0|2024-03-14|
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|65|[lgy0404/d2l-2023](https://github.com/lgy0404/d2l-2023)|✔️（持续更新）李沐 【动手学深度学习v2 PyTorch版】课程学习笔记，更正了AccumulateMore笔记的部分错误，从更加初级的角度做了部分内容补充|29|0|2023-09-21|
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|66|[hitlic/python_book](https://github.com/hitlic/python_book)|清华大学出版社《Python从入门到提高》源代码、课件|36|0|2024-02-01|
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|67|[ruoxining/ZJU_COURSE_MATERIALS](https://github.com/ruoxining/ZJU_COURSE_MATERIALS)|ZJU课程资料，主要含英语+CS专业课，不含不合适公开的资料和违反honor code的作业|39|0|2024-01-18|
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|68|[HugoBlox/theme-blog](https://github.com/HugoBlox/theme-blog)|📝 Hugo Academic Blog Theme. 轻松创建一个简约博客. No code, highly customizable using widgets.|99|0|2024-03-03|
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|69|[binzhouchn/machine_learning](https://github.com/binzhouchn/machine_learning)|抽象来讲，机器学习问题是把数据转换成信息再提炼到知识的过程，特征是“数据-->信息”的过程，决定了结果的上限，而分类器是“信息-->知识”的过程，则是去逼近这个上限|19|0|2024-01-23|
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|70|[sijichun/MathStatsCode](https://github.com/sijichun/MathStatsCode)|Codes for my mathematical statistics course|168|0|2023-12-17|
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|71|[loveunk/machine-learning-deep-learning-notes](https://github.com/loveunk/machine-learning-deep-learning-notes)|机器学习、深度学习的学习路径及知识总结|893|0|2024-01-09|
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|72|[sfvsfv/Crawer](https://github.com/sfvsfv/Crawer)|《Python网络爬虫入门到实战》配套程序。爬虫项目集合，|17|0|2023-11-03|
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|73|[microsoft/AIforEarthDataSets](https://github.com/microsoft/AIforEarthDataSets)|Notebooks and documentation for AI-for-Earth-managed datasets on Azure|261|0|2023-11-29|
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|74|[neolee/wop](https://github.com/neolee/wop)|零基础编程思维与实践课程《欢迎进入编程世界》主站|79|0|2023-09-30|
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|75|[hacheyz/PMMAA](https://github.com/hacheyz/PMMAA)|《Python 数学建模算法与应用》- 司守奎，知识点笔记 & 代码 (Python Mathematical Modeling)|56|0|2023-12-23|
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|76|[AccumulateMore/Python](https://github.com/AccumulateMore/Python)|✔（已完结）最全面的 Python 笔记【马士兵教育】|299|0|2023-09-27|
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|77|[IKMLab/course_material](https://github.com/IKMLab/course_material)|上課教材的大集合！！！|53|0|2024-02-26|
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|78|[kingname/SourceCodeofMongoRedis](https://github.com/kingname/SourceCodeofMongoRedis)|《左手MongoDB，右手Redis——从入门到商业实战》书籍配套源代码。|205|0|2024-02-17|
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|79|[zju-isee/zju-isee](https://github.com/zju-isee/zju-isee)|浙江大学电子科学与技术专业部分课程仓库|167|0|2023-12-05|
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|80|[2811668688/ZJU-CS](https://github.com/2811668688/ZJU-CS)|这里是我对浙江大学混合班CS的一些课程的资料整理，希望能给予看到的朋友一些帮助。|101|0|2023-11-06|
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|81|[AccumulateMore/CPlusPlus](https://github.com/AccumulateMore/CPlusPlus)|✔（已完结）最全面的 C++ 笔记 【黑马程序员】|402|0|2023-09-27|
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|82|[jinhualee/datashine](https://github.com/jinhualee/datashine)|《Python统计与数据分析实战》课程代码，包含了大部分统计与非参数统计和数据分析的模型、算法。回归分析、方差分析、点估计、假设检验、主成分分析、因子分析、聚类分析、判别分析、对数线性模型、分位回归模型以及列联表分析、非参数平滑、非参数密度估计等各种非参数统计方法。|271|0|2024-03-17|
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|83|[hxchua/datadoubleconfirm](https://github.com/hxchua/datadoubleconfirm)|Simple datasets and notebooks for data visualization, statistical analysis and modelling - with write-ups here: http://projectosyo.wix.com/datadoubleconfirm. |53|0|2023-11-21|
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|84|[WYGNG/USTC_SSE_Python](https://github.com/WYGNG/USTC_SSE_Python)|中国科学技术大学软件学院python程序设计课程|35|0|2023-10-26|
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|85|[yenlung/Python-AI-Book](https://github.com/yenlung/Python-AI-Book)|《少年Py的大冒險》第二集, 深度學習的入門!|42|0|2023-12-19|
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|86|[AccumulateMore/Spider](https://github.com/AccumulateMore/Spider)|✔（已完结）最全面的 爬虫与数据库 笔记|42|0|2023-09-27|
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|87|[ScienceLi1125/CQU-Study](https://github.com/ScienceLi1125/CQU-Study)|重庆大学计算机学院学习资料|68|0|2023-12-11|
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|88|[wklchris/blog](https://github.com/wklchris/blog)|个人 Github.io 站点上的博客文章 Blogs on my Github.io site|22|0|2023-10-15|
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|89|[lingwsh/ben_tech_python](https://github.com/lingwsh/ben_tech_python)|小白学Python课程资料|32|0|2023-12-31|
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|90|[dmarx/anthology-of-modern-ml](https://github.com/dmarx/anthology-of-modern-ml)|Collection of important articles to be treated as a textbook|375|0|2024-02-14|
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|91|[LinglingGreat/StudySum](https://github.com/LinglingGreat/StudySum)|学习过程中的笔记梳理与总结|20|0|2024-01-16|
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|92|[coggle-club/notebooks](https://github.com/coggle-club/notebooks)|数据科学教程案例|15|0|2024-01-17|
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|93|[CloneNOX/MSA-BiGCN](https://github.com/CloneNOX/MSA-BiGCN)|中山大学2022届本科生毕业论文《基于注意力机制和图卷积神经网络的多任务谣言检测》代码实现和baseline代码。现采用BERT作为编码器，实现了新的模型。|29|0|2024-03-17|
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|94|[newaetech/chipwhisperer-jupyter](https://github.com/newaetech/chipwhisperer-jupyter)|Interactive ChipWhisperer tutorials using Jupyter notebooks.|191|0|2024-01-19|
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|95|[chen2438/zstu-study](https://github.com/chen2438/zstu-study)|zstu 浙江理工大学 学习资料|22|0|2024-03-13|
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|96|[Hoper-J/HUNG-YI_LEE_Machine-Learning_Homework](https://github.com/Hoper-J/HUNG-YI_LEE_Machine-Learning_Homework)|李宏毅 (HUNG-YI LEE）机器学习作业思路代码分享|62|0|2023-11-19|
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|97|[limingzhong61/LearningNotes](https://github.com/limingzhong61/LearningNotes)|学习笔记|36|0|2023-10-27|
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|98|[qq31682216/chatgpt_all](https://github.com/qq31682216/chatgpt_all)|学习开源chatGPT类模型的指南，汇总各种训练数据获取、模型微调、模型服务的方法，以及记录自己操作总遇到的各种常见坑，欢迎收藏、转发，希望能帮你省一些时间|57|0|2023-10-05|
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|99|[JamesLavin/my_tech_resources](https://github.com/JamesLavin/my_tech_resources)|List of tech resources future me and other Javascript/Ruby/Python/Elixir/Elm developers might find useful|305|0|2024-03-05|
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|100|[datawhalechina/hands-dirty-nlp](https://github.com/datawhalechina/hands-dirty-nlp)|本课程面对具有一定机器学习基础，但尚未入门的NLPer或经验尚浅的NLPer，尽力避免陷入繁琐枯燥的公式讲解中，力求用代码展示每个模型背后的设计思想，同时也会带大家梳理每个模块下的技术演变，做到既知树木也知森林。|72|0|2023-12-17|
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|101|[Robin-WZQ/BIT-AI-Review](https://github.com/Robin-WZQ/BIT-AI-Review)|本项目分享了本人在北京理工大学计算机学院人工智能专业的相关课程资料与经验分享。希望对你们有所帮助❤️，如果喜欢的话记得给个star哦🌟|120|0|2024-01-14|
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|102|[pangbo13/Courses](https://github.com/pangbo13/Courses)|本项目保存了本人在上海交通大学计算机科学与技术专业部分课程学习过程中的作业与项目代码。|20|0|2024-03-10|
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|103|[shuliu586/AI_Chinese_DataSet_KnowledgeDAO](https://github.com/shuliu586/AI_Chinese_DataSet_KnowledgeDAO)|供AI训练的中文数据集（持续更新。。。）与AI公司图谱，目前的数据集餐饮行业8000问，百度知道，Alpaca中文数据集，计算机领域数据集，Vicuna数据集，RedPajama数据集，Wikipedia中文词条数据集，网站论坛问答数据集|43|0|2023-11-29|
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|104|[Kedreamix/Pytorch-Image-Classification](https://github.com/Kedreamix/Pytorch-Image-Classification)|用于pytorch的图像分类，包含多种模型方法，比如AlexNet，VGG，GoogleNet，ResNet，DenseNet等等，包含可完整运行的代码。除此之外，也有colab的在线运行代码，可以直接在colab在线运行查看结果。也可以迁移到自己的数据集进行迁移学习。|142|0|2023-12-07|
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|105|[CyberZHG/CLRS](https://github.com/CyberZHG/CLRS)|Some exercises and problems in Introduction to Algorithms 3rd edition.|418|0|2024-03-02|
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|106|[LecterChu/nwpu-cram](https://github.com/LecterChu/nwpu-cram)|西北工业大学/西工大/nwpu/npu软件学院复习(突击)资料！！|156|0|2024-03-02|
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|107|[hwdqm88/pattern-recognition-807](https://github.com/hwdqm88/pattern-recognition-807)|《模式识别（第三版）》（张学工）学习笔记+2024真题，清华大学深圳研究生院人工智能专业考研807专业课|35|0|2024-03-13|
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|108|[Allenpandas/BJTU-SCIT-Notebook](https://github.com/Allenpandas/BJTU-SCIT-Notebook)|👨🎓 北京交通大学计算机与信息技术学院研究生课程资料、笔记、回忆和整理的期末考试卷及课程作业。希望对你们有所帮助❤️，如果喜欢记得给个star🌟|51|0|2024-02-19|
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|109|[wx-chevalier/Mathematics-Notes](https://github.com/wx-chevalier/Mathematics-Notes)|:books: [.md & .ipynb] 人工智能与深度学习实战--数理统计与数据分析篇|31|0|2024-02-12|
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|110|[logan-zou/Tutorial_for_developing_LLM_application](https://github.com/logan-zou/Tutorial_for_developing_LLM_application)|一个面向小白的大模型应用开发课程|26|0|2023-10-30|
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|111|[rwepa/DataDemo](https://github.com/rwepa/DataDemo)|提供資料集與範例分享.|17|0|2023-12-27|
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|112|[yuyou-dev/ChatGPT-Fine-tuning](https://github.com/yuyou-dev/ChatGPT-Fine-tuning)|Quick-start guide to fine-tuning ChatGPT using Python. Includes scripts for data preprocessing, model training, and evaluation. 快速入门指南: 使用Python微调ChatGPT。包含数据预处理、模型训练和评估脚本。|22|0|2023-11-29|
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|113|[cumtcssuld/RSP_of_CUMTCS](https://github.com/cumtcssuld/RSP_of_CUMTCS)|【矿大计算机学院资源共享计划（Resource SharingPlan of CUMTCS）】本仓库由矿大计算机学院学生会学习部牵头维护，由计算机学院全体同学共建共享。欢迎大家积极的参加到本资源库的建设中来吧！（每当有重大更新，我们都会将整个库克隆到码云，点击下边链接，到我们的码云仓库可以获得更好的下载体验）|86|0|2023-10-03|
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|114|[charliedream1/ai_wiki](https://github.com/charliedream1/ai_wiki)|AI实践：各类知识和样例汇总，包括大模型、编程、机器学习、 深度学习、强化学习、图神经网络，语音识别、NLP和图像识别等|56|0|2024-03-17|
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|115|[gkm0120/Graph-Neural-Network-Papers](https://github.com/gkm0120/Graph-Neural-Network-Papers)|图神经网络、图卷积网络、图注意力网络、图自编码网络、时空图神经网络等论文合集。|81|0|2024-02-27|
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|116|[Gengzhige/Deep-Learning-Code](https://github.com/Gengzhige/Deep-Learning-Code)|《深度学习必修课：进击算法工程师》配套代码|26|0|2024-01-06|
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|117|[ChileWang0228/Deep-Learning-With-Python](https://github.com/ChileWang0228/Deep-Learning-With-Python)|《Python深度学习》书籍代码|599|0|2024-01-30|
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|118|[fan2goa1/BIT-CS-UnderGraduate](https://github.com/fan2goa1/BIT-CS-UnderGraduate)|这个仓库存放了北京理工大学计科专业相关课程资料，欢迎Star & PR。|36|0|2024-01-11|
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|119|[muchuang1024/python-examples](https://github.com/muchuang1024/python-examples)|我的python语言学习代码|28|0|2023-11-27|
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|120|[batermj/data_sciences_campaign](https://github.com/batermj/data_sciences_campaign)|【数据科学家系列课程】|97|0|2024-03-16|
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|121|[datawhalechina/wow-fullstack](https://github.com/datawhalechina/wow-fullstack)|wow-fullstack，令人惊叹的全栈开发教程|29|0|2024-03-17|
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|122|[zui0711/Z-Lab](https://github.com/zui0711/Z-Lab)|Z Lab数据实验室开源代码汇总|175|0|2024-02-27|
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|123|[WangRongsheng/Use-LLMs-in-Colab](https://github.com/WangRongsheng/Use-LLMs-in-Colab)|🤖 集合众多大模型在Colab上的使用 LLMs is all you need.|105|0|2023-11-06|
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|124|[wanZzz6/Modules-Learn](https://github.com/wanZzz6/Modules-Learn)|学习笔记 - 码云：https://gitee.com/wanzheng_96/Modules-Learn）|320|0|2023-11-01|
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|125|[ConnectAI-E/LangChain-Tutior](https://github.com/ConnectAI-E/LangChain-Tutior)|⛓ LangChain 入门指南，配套吴恩达老师deeplearning.ai课程 😎复现语言：Python、NodeJs、Golang|77|0|2024-01-03|
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|126|[HuichuanLI/GraphNeuralNetWork](https://github.com/HuichuanLI/GraphNeuralNetWork)|玩转图神经网络和知识图谱的相关算法：GCN,GAT,GAFM,GAAFM,GraphSage,W2V,TRANSe|21|0|2024-02-25|
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|127|[fire717/Machine-Learning](https://github.com/fire717/Machine-Learning)|机器学习&深度学习资料笔记&基本算法实现&资源整理（ML / CV / NLP / DM...）|208|0|2024-02-05|
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|128|[Winn1y/Show2Know](https://github.com/Winn1y/Show2Know)|基于科研论文导向的可视化绘图集锦|27|0|2024-02-23|
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|129|[analyticalmindsltd/smote_variants](https://github.com/analyticalmindsltd/smote_variants)|A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features|582|0|2024-01-03|
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|130|[AI4Finance-Foundation/FinRL-Tutorials](https://github.com/AI4Finance-Foundation/FinRL-Tutorials)|Tutorials. Please star. |669|0|2024-03-15|
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|131|[xiaomeng79/learning_notes](https://github.com/xiaomeng79/learning_notes)|学习笔记|21|0|2024-03-12|
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|132|[liangruibupt/aws-is-how](https://github.com/liangruibupt/aws-is-how)|Know How Guide and Hands on Guide for AWS|38|0|2024-03-17|
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|133|[OneStepAndTwoSteps/Data_Analysis_notes](https://github.com/OneStepAndTwoSteps/Data_Analysis_notes)|📖 Machine learning algorithms and deep learning algorithms|26|0|2023-10-12|
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|134|[Ifan24/GPT_subtitles](https://github.com/Ifan24/GPT_subtitles)|Download YouTube video (or supply your own) and generate dual languange subtitles with OpenAI Whisper and translation API (GPT) 下载 YouTube 视频（或提供您自己的视频）并使用 Whisper 和翻译AP ...|57|0|2024-01-03|
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|135|[unimauro/QuantumResources](https://github.com/unimauro/QuantumResources)|Here Quantum Resources like: Book, Papers, Videos|25|0|2024-01-02|
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|136|[ForeverHaibara/Fudan-Courses](https://github.com/ForeverHaibara/Fudan-Courses)|Notes for Courses in School of Data Science, Fudan University. 复旦大学数据科学与大数据技术专业（复旦大数据）学习笔记。|70|0|2023-11-13|
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|137|[bobo0810/PytorchNetHub](https://github.com/bobo0810/PytorchNetHub)|项目注释+论文复现+算法竞赛+Pytorch实践|587|0|2024-02-18|
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|138|[zkywsg/Daily-DeepLearning](https://github.com/zkywsg/Daily-DeepLearning)|🔥机器学习/深度学习/Python/算法面试/自然语言处理教程/剑指offer/machine learning/deeplearning/Python/Algorithm interview/NLP Tutorial|537|0|2024-01-17|
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|139|[HuangCongQing/3D-Point-Clouds](https://github.com/HuangCongQing/3D-Point-Clouds)|🔥3D点云目标检测&语义分割(深度学习)-SOTA方法,代码,论文,数据集等|344|0|2024-02-12|
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|140|[NAOSI-DLUT/DLUT_ISE_Courses](https://github.com/NAOSI-DLUT/DLUT_ISE_Courses)|大连理工大学软国专业课程指南,请同学们踊跃发言和@dingsio|18|0|2023-11-20|
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|141|[RiverTwilight/Awesome-Machine-Learning-Playground](https://github.com/RiverTwilight/Awesome-Machine-Learning-Playground)|🌟 Dive into the world of machine learning with three no-framework, beginner-friendly models. 基于项目的机器学习入门理论详解。|24|0|2023-10-27|
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|142|[W-caner/ML_class](https://github.com/W-caner/ML_class)|学堂在线《机器学习》实验课by张敏老师|21|0|2023-11-26|
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|143|[ZitongLu1996/Python-EEG-Handbook-CN](https://github.com/ZitongLu1996/Python-EEG-Handbook-CN)|Python脑电数据处理中文手册 - A Chinese handbook for EEG data analysis based on Python|258|0|2024-03-14|
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|144|[HITSZ-OpenAuto/PHYS1002A](https://github.com/HITSZ-OpenAuto/PHYS1002A)|HITSZ 大学物理实验IA 实验报告、数据处理及绘图程序等资料|27|0|2024-03-17|
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|145|[aihes/LangChain-Tutorials-and-Examples](https://github.com/aihes/LangChain-Tutorials-and-Examples)|LangChain结合了大型语言模型、知识库和计算逻辑，可以用于快速开发强大的AI应用。这个仓库包含了我对LangChain的学习和实践经验，包括教程和代码案例。让我们一起探索LangChain的可能性，共同推动人工智能领域的进步！|54|0|2023-09-21|
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|146|[sangyx/gtrick](https://github.com/sangyx/gtrick)|Bag of Tricks for Graph Neural Networks.|265|0|2023-10-23|
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|147|[aialgorithm/Blog](https://github.com/aialgorithm/Blog)|Python机器学习算法技术博客，有原创干货！有code实践！ 【更多内容敬请关注公众号 "算法进阶"】|678|0|2024-02-27|
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|148|[zhangjunhd/reading-notes](https://github.com/zhangjunhd/reading-notes)|张俊的读书笔记|272|0|2024-03-10|
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|149|[dream80/TonyColab](https://github.com/dream80/TonyColab)|Colab script collection for various amazing projects! 各种牛逼项目的Colab脚本集合！|160|0|2024-02-23|
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|150|[NJUPTFreeExams/NJUPT-General-Free-Exams](https://github.com/NJUPTFreeExams/NJUPT-General-Free-Exams)|南京邮电大学通识课程历年资料。|462|0|2024-02-02|
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|151|[Michael-Jetson/ML_DL_CV_with_pytorch](https://github.com/Michael-Jetson/ML_DL_CV_with_pytorch)|一个计算机视觉、机器学习与深度学习相关的项目，看课程的笔记还有自己做的程序|94|0|2023-12-31|
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|152|[stuser/temp](https://github.com/stuser/temp)|公開分享檔案暫存區|20|0|2023-12-07|
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|153|[AccumulateMore/NLP](https://github.com/AccumulateMore/NLP)|✔最全面的 深度学习NLP 笔记|35|0|2023-09-27|
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|154|[Relph1119/my-team-learning](https://github.com/Relph1119/my-team-learning)|我的Datawhale组队学习，在线阅读地址：https://relph1119.github.io/my-team-learning|53|0|2024-03-03|
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|155|[yujunkuo/ML2022-Homework](https://github.com/yujunkuo/ML2022-Homework)|[機器學習 110-2@NTU] 課程作業|23|0|2023-12-20|
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<p><sub>↓ -- 感谢读者 -- ↓</sub></p>
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榜单持续更新，如有帮助请加星收藏，方便后续浏览，感谢你的支持！
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<div align="center"><a href="https://github.com/GrowingGit/GitHub-Chinese-Top-Charts#github中文排行榜">返回目录</a> • <a href="/content/docs/feedback.md">问题反馈</a></div>
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