AI Job Seeker — Data skill for Claude Code
Job market analytics, salary prediction, and personalized recommendations for smarter job hunting.
How to install AI Job Seeker
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open sunflower0305/ai-job-seeker and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What AI Job Seeker does
Job market analytics, salary prediction, and personalized recommendations for smarter job hunting.
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README
[](https://zread.ai/sunflower0305/ai-job-seeker) [](https://job.zhangleyang.com)
AI 求职助手
把求职里最常见的几件事放到同一个系统里:上传简历、分析岗位、推荐职位、预测薪资、优化简历、导出文档。
项目简介
本系统是一个完整的招聘数据分析解决方案,通过爬虫技术获取招聘网站数据,利用数据分析和机器学习技术,为求职者提供薪资分析、职位推荐、薪资预测等功能。
核心功能
1. 数据获取
- 爬取主流招聘网站职位数据(智联招聘/前程无忧/Boss 直聘)
- 支持多线程/异步爬取
- 反爬策略处理
2. 数据清洗与分析
- 薪资数据标准化
- 缺失值和异常值处理
- 多维度统计分析(城市、学历、经验、行业等)
3. 数据可视化
- 城市薪资分布地图
- 薪资/学历/经验分布图表
- 技能词云图
- 行业/公司规模分析
4. 机器学习
- 职位推荐:基于 TF-IDF 和余弦相似度的推荐算法
- 薪资预测:使用随机森林/逻辑回归预测薪资区间
5. 用户系统
- 用户注册/登录
- 个人信息管理
- 浏览历史记录
- 职位收藏功能
技术栈
后端
- 框架:Django 4.2
- 数据库:MySQL 8.0
- ORM:SQLAlchemy
数据处理
- 爬虫:Requests + BeautifulSoup4 + Selenium + Scrapy
- 分析:Pandas + NumPy
- 可视化:Matplotlib + Seaborn + WordCloud
机器学习
- 框架:Scikit-learn
- NLP:Jieba(中文分词)
- 算法:TF-IDF、余弦相似度、随机森林、逻辑回归
前端
- 基础:HTML5 + CSS3 + JavaScript
- 图表:ECharts
- UI 框架:Bootstrap
项目结构
ai-job-seeker/
├── manage.py # Django 管理入口
├── start.sh / stop.sh # 本地启动与停止脚本
├── job_platform/ # Django 项目配置
├── jobs/ # 职位、分析、文档生成相关应用
├── users/ # 用户、权限、访问日志相关应用
├── recommendations/ # 推荐相关应用
├── crawler/ # 爬虫核心模块
├── data_process/ # 数据清洗、分析、可视化模块
├── ml_models/ # 机器学习模型
├── frontend/ # Next.js 前端
├── scripts/
│ ├── crawlers/ # 爬虫运行、Cookie、页面诊断脚本
│ └── data/ # 数据导入、清理、检查、初始化脚本
├── tests/manual/ # 手动/集成验证脚本
├── docs/
│ ├── guides/ # 使用和功能指南
│ └── reports/ # 阶段性报告和修复记录
├── reports/ # JSON 等运行报告输出
├── runtime/ # PID 等运行时文
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