{"id":15008841,"url":"https://github.com/tingnie/machine-learning-in-action","last_synced_at":"2025-08-10T16:09:20.616Z","repository":{"id":107577756,"uuid":"111105342","full_name":"TingNie/Machine-learning-in-action","owner":"TingNie","description":"个人使用jupyter notebook整理的peter的《机器学习实战》代码，使其更有层次感，更加连贯，也加了一些自己的修改，以及注释","archived":false,"fork":false,"pushed_at":"2018-01-06T05:43:16.000Z","size":2627,"stargazers_count":299,"open_issues_count":0,"forks_count":143,"subscribers_count":9,"default_branch":"master","last_synced_at":"2025-05-20T05:02:05.611Z","etag":null,"topics":["jupyter-notebook","machine-learning","python2"],"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/TingNie.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-11-17T13:16:28.000Z","updated_at":"2025-05-09T03:11:02.000Z","dependencies_parsed_at":null,"dependency_job_id":"ac38c1fe-0d74-42d0-a382-a792837ce2ff","html_url":"https://github.com/TingNie/Machine-learning-in-action","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/TingNie/Machine-learning-in-action","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TingNie%2FMachine-learning-in-action","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TingNie%2FMachine-learning-in-action/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TingNie%2FMachine-learning-in-action/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TingNie%2FMachine-learning-in-action/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TingNie","download_url":"https://codeload.github.com/TingNie/Machine-learning-in-action/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TingNie%2FMachine-learning-in-action/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269748230,"owners_count":24469107,"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","status":"online","status_checked_at":"2025-08-10T02:00:08.965Z","response_time":71,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["jupyter-notebook","machine-learning","python2"],"created_at":"2024-09-24T19:20:55.269Z","updated_at":"2025-08-10T16:09:20.582Z","avatar_url":"https://github.com/TingNie.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine-learning-in-action\n个人使用jupyter notebook整理的**peter的《机器学习实战》代码**，使其更有层次感，更加连贯，也根据自己的代码习惯，加了一些自己的修改，以及注释\n\n这是给自己做的笔记，贴出来，也是希望大家一起学习!\n\n**注**：原版所有代码[点击这里](https://www.manning.com/books/machine-learning-in-action)        GitHub整理的资源[apachecn/MachineLearning](https://github.com/apachecn/MachineLearning)\n\n内容包括：\n---\n\nadaBoost文件夹：AdaBoost元算法提高分类性能\n\napriori文件夹：Apriori算法进行关联分析\n\nbayes文件夹：bayes算法用于垃圾邮件分类\n\ndecisionTree文件夹：使用决策树算法，进行数据分类\n\nfp-growth文件夹：FP-growth算法加速发现频繁项集\n\nkmeans文件夹：kmeans + 二分kmeans算法\n\nk-Nearest Neighbor文件夹：k近邻算法 + 数值归一化\n\nlogistic文件夹：batch GD + SGD\n\npca文件夹：pca降维\n\npca和svd的比较：关于pca和svd的区别和联系，理论参见[博客](http://blog.csdn.net/dark_scope/article/details/53150883)\n\nregress文件夹：线性回归 + 局部加权线性回归 + 岭回归 + 向前逐步回归 \n\nregressionTree文件夹：回归树+模型树\n\nsvd文件夹：svd降维 + 协同过滤算法进行物品推荐\n\nsvm文件夹：简化版smo实现svm(支持向量机)分类器\n\n# 完结\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftingnie%2Fmachine-learning-in-action","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftingnie%2Fmachine-learning-in-action","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftingnie%2Fmachine-learning-in-action/lists"}