{"id":20673013,"url":"https://github.com/relph1119/statistical-learning-method-camp","last_synced_at":"2026-03-14T14:55:05.418Z","repository":{"id":37220128,"uuid":"168173623","full_name":"Relph1119/statistical-learning-method-camp","owner":"Relph1119","description":"统计学习方法训练营课程作业及答案，视频笔记在线阅读地址：https://relph1119.github.io/statistical-learning-method-camp","archived":false,"fork":false,"pushed_at":"2022-11-22T06:37:11.000Z","size":47554,"stargazers_count":196,"open_issues_count":11,"forks_count":77,"subscribers_count":11,"default_branch":"master","last_synced_at":"2025-03-24T08:08:21.767Z","etag":null,"topics":["statistical-learning"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Relph1119.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-01-29T15:01:19.000Z","updated_at":"2025-03-21T07:38:25.000Z","dependencies_parsed_at":"2023-01-21T07:02:05.783Z","dependency_job_id":null,"html_url":"https://github.com/Relph1119/statistical-learning-method-camp","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fstatistical-learning-method-camp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fstatistical-learning-method-camp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fstatistical-learning-method-camp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fstatistical-learning-method-camp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Relph1119","download_url":"https://codeload.github.com/Relph1119/statistical-learning-method-camp/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246922247,"owners_count":20855345,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["statistical-learning"],"created_at":"2024-11-16T20:39:48.162Z","updated_at":"2026-03-14T14:55:00.378Z","avatar_url":"https://github.com/Relph1119.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 《统计学习方法》训练营\n\n## 课程资料\n- [ApacheCN](https://ailearning.apachecn.org/)\n- [廖雪峰 Python3 教程](https://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000)\n- 优秀github资源：  \n1. [李航《统计学习方法》中机器学习模型的LaTeX公式笔记](https://github.com/anch3or/Machine-Learning-Notes)  \n2. [李航《统计学习方法笔记》中的代码、notebook、参考文献、Errata](https://github.com/SmirkCao/Lihang)  \n3. [李航《统计学习方法》习题笔记](https://sine-x.com/statistical-learning-method)\n- 本训练营的学习安排与课程任务：详见文件夹Books中的《统计学习方法作业》doc文档\n\n## 视频笔记在线阅读地址\n视频笔记在线阅读地址：https://relph1119.github.io/statistical-learning-method-camp\n\n## 相关资料下载地址（包括视频笔记和习题解答）\n链接：https://pan.baidu.com/s/1TrUW79J06HzVRoqOebLg9w  \n提取码：tc49  \n\n## 课程安排（第四期）\n**总课时：5 周**\n\n### 第一周\n- 1 学习第1章统计学习方法概论\n- 2 学习第2章感知机\n- 3 学习第3章k近邻\n\n### 第二周\n- 4 学习第4章朴素贝叶斯法\n- 5 学习第5章决策树\n\n### 第三周\n- 6 学习第6章Logistic回归与最大熵模\n- 7 学习第7章支持向量机\n\n### 第四周\n- 8 学习第8章提升方法\n- 9 学习第9章EM算法及推广\n\n### 第五周\n- 10 学习第10章隐马尔科夫模型\n- 11 学习第11章条件随机场\n\n## 项目结构\n\u003cpre\u003e\nBooks--------------------------------------作业汇总和视频笔记的pdf\ndocs---------------------------------------视频笔记\nExercises-of-the-First-Edition-------------第一版章节习题解答\n+---images---------------------------------习题插图\n+---notebook-------------------------------JupyterNotebook格式习题解答\nPhaseFour----------------------------------深度之眼第四期\n+---Note\n|    +----image----------------------------笔记截图\n|    +----notebook-------------------------JupyterNotebook格式视频笔记\n+---Week1----------------------------------第一周作业\n+---Week2----------------------------------第二周作业\n+---Week3----------------------------------第三周作业\n+---Week4----------------------------------第四周作业\n+---Week5----------------------------------第五周作业\nPhaseOne-----------------------------------深度之眼第一期\n+---Week1----------------------------------第一周作业\n+---Week2----------------------------------第二周作业\n+---Week3----------------------------------第三周作业\n+---Week4----------------------------------第四周作业\n+---Week5----------------------------------第五周作业\n\u003c/pre\u003e\n\n## 运行环境设置\n1. 安装相关的依赖包\n    ```shell\n    pip install -r requirements.txt\n    ```\n2. 安装graphviz  \n    可参考博客：https://blog.csdn.net/HNUCSEE_LJK/article/details/86772806\n3. 设置PhaseFour目录为Sources Root\n\n## 总结\n\u0026emsp;\u0026emsp;笔者有一些作业题是根据优秀资源[3]中解答的，作业题并不难，希望小伙伴们都能动手完成。  \n\u0026emsp;\u0026emsp;该训练营课程来自微信公众号深度之眼，笔者非常推荐，虽然以自学为主，但是在星球中能学到很多知识。该公众号下的机器学习实战训练营也很不错，大家可以尝试学习一下，一定有很大的收获。这个是我在该训练营的作业：[机器学习实战](https://github.com/Relph1119/MachineLearningInAction-Camp)  \n\u0026emsp;\u0026emsp;笔者用了近三周时间（2019年7月26日——2019年8月15日），完成了深度之眼的统计学习方法第四期视频笔记，再次学一遍感觉收获甚多，还记得第一次学这本书的时候，很多公式都没有手动推导，这次视频笔记是根据老师的视频，添加了很多笔者自己推导的公式，希望大家能读懂并能有所收获，笔记中难免有些错误，还请大家能协助帮忙指出。  \n\u0026emsp;\u0026emsp;笔者用了近10天时间（2019年11月4日——2019年11月14日），完成了李航-统计学习方法（第一版）的[所有习题](https://github.com/datawhalechina/statistical-learning-method-solutions-manual)，在做习题的时候，查了很多资料，大部分题目是参考优秀资源[3]中的解答，虽然里面很多证明没有，但是笔者依然坚持完成了，这是第三遍刷李航老师的这本书了，笔记中习题6.3的代码编程没有完成，但是笔者依然会在后期完善并更新文档，PDF版本在Books文件夹下，另外很感谢一个女生一直支持我完成习题。","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frelph1119%2Fstatistical-learning-method-camp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frelph1119%2Fstatistical-learning-method-camp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frelph1119%2Fstatistical-learning-method-camp/lists"}