{"id":14958657,"url":"https://github.com/honlan/deepinterests","last_synced_at":"2025-05-15T17:04:27.213Z","repository":{"id":201292445,"uuid":"125862390","full_name":"Honlan/DeepInterests","owner":"Honlan","description":"深度有趣","archived":false,"fork":false,"pushed_at":"2020-08-20T08:34:51.000Z","size":36510,"stargazers_count":2291,"open_issues_count":0,"forks_count":419,"subscribers_count":91,"default_branch":"master","last_synced_at":"2025-04-07T22:07:47.527Z","etag":null,"topics":["artificial-intelligence","computer-vision","deep-learning","keras","mit-license","natural-language-processing","python","tensorflow"],"latest_commit_sha":null,"homepage":null,"language":null,"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/Honlan.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}},"created_at":"2018-03-19T13:31:41.000Z","updated_at":"2025-03-05T12:03:27.000Z","dependencies_parsed_at":null,"dependency_job_id":"3e9fcb8a-2259-47f2-b73e-248a31461dd8","html_url":"https://github.com/Honlan/DeepInterests","commit_stats":null,"previous_names":["honlan/deepinterests"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Honlan%2FDeepInterests","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Honlan%2FDeepInterests/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Honlan%2FDeepInterests/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Honlan%2FDeepInterests/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Honlan","download_url":"https://codeload.github.com/Honlan/DeepInterests/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254384987,"owners_count":22062422,"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":["artificial-intelligence","computer-vision","deep-learning","keras","mit-license","natural-language-processing","python","tensorflow"],"created_at":"2024-09-24T13:17:45.022Z","updated_at":"2025-05-15T17:04:22.195Z","avatar_url":"https://github.com/Honlan.png","language":null,"readme":"# DeepInterests\n\n### 深度有趣 - 人工智能实战项目合集\n\n使用Python3、TensorFlow1.9和Keras2.2，课程介绍文章，[https://zhuanlan.zhihu.com/p/34744472](https://zhuanlan.zhihu.com/p/34744472)。\n\n- Github项目：[https://github.com/Honlan/DeepInterests](https://github.com/Honlan/DeepInterests)，包括182页的课程说明文档pdf；\n- 项目网盘：[https://pan.baidu.com/s/1edrdM1xHMc9DTI7WkGweQA](https://pan.baidu.com/s/1edrdM1xHMc9DTI7WkGweQA)，密码m3we，包括数据和代码，分为完整版和精简版两个版本，前者包括项目所涉及的完整内容，后者只包括最后执行所需的必要文件；\n- 知乎专栏：[https://zhuanlan.zhihu.com/DeepInterests](https://zhuanlan.zhihu.com/DeepInterests)，包括在线版的文档和代码；\n- 付费视频：[https://study.163.com/course/courseMain.htm?courseId=1004777011](https://study.163.com/course/courseMain.htm?courseId=1004777011)，让你更好、更快、更轻松、更全面的掌握每一个项目。\n\n献给每一个有趣的灵魂。\n\n![](宣传.png)\n\n### 课程特点\n\n- 精彩绝伦的实战项目合集；\n- 匠心打造、诚意出品；\n- 开源！开源！开源！\n\n### 前置课程\n\n- 《Python基础入门》：[https://study.163.com/course/courseMain.htm?courseId=1005461017](https://study.163.com/course/courseMain.htm?courseId=1005461017)，我出的Python入门课，面向零编程基础的同学，主要讲解Python核心语法；\n- 《深度学习微专业》，[https://mooc.study.163.com/smartSpec/detail/1001319001.htm](https://mooc.study.163.com/smartSpec/detail/1001319001.htm)，吴恩达老师出的深度学习理论课，内容全面而有深度，对掌握深度学习各方面理论知识很有帮助；\n- 《全栈数据工程师养成攻略》：[https://study.163.com/course/courseMain.htm?courseId=1003520028](https://study.163.com/course/courseMain.htm?courseId=1003520028)，我出的Python实战课，从采集、存储、分析和可视化等角度讲解如何用Python实现一些数据项目，有助于提升个人编程能力。\n\n### 课程目录\n\n01. 前言\n02. 准备工作\n03. 高端又一般的词云\n04. 图像风格迁移\n05. 自编码器图像去噪\n06. 变分自编码器\n07. 生成式对抗网络\n08. 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