# HR-Analytics-from-Kaggle
This challenge can be found in Kaggle in case you want to see other notebooks and solutions as well:
https://www.kaggle.com/arashnic/hr-analytics-job-change-of-data-scientists
## Context and Content
A company which is active in Big Data and Data Science wants to hire data scientists among people who successfully pass some courses which conduct by the company. Many people signup for their training. Company wants to know which of these candidates are really wants to work for the company after training or looking for a new employment because it helps to reduce the cost and time as well as the quality of training or planning the courses and categorization of candidates. Information related to demographics, education, experience are in hands from candidates signup and enrollment.
This dataset designed to understand the factors that lead a person to leave current job for HR researches too. By model(s) that uses the current credentials,demographics,experience data you will predict the probability of a candidate to look for a new job or will work for the company, as well as interpreting affected factors on employee decision.
The whole data divided to train and test . Target isn't included in test but the test target values data file is in hands for related tasks. A sample submission correspond to enrollee_id of test set provided too with columns : enrollee _id , target
## Note:
The dataset is imbalanced. Most features are categorical (Nominal, Ordinal, Binary), some with high cardinality. Missing imputation can be a part of your pipeline as well. Features
enrollee_id : Unique ID for candidate
city: City code
city_ development _index : Developement index of the city (scaled)
gender: Gender of candidate
relevent_experience: Relevant experience of candidate
enrolled_university: Type of University course enrolled if any
education_level: Education level of candidate
major_discipline :Education major discipline of candidate
experience: Candidate total experience in years
company_size: No of employees in current employer's company
company_type : Type of current employer
lastnewjob: Difference in years between previous job and current job
training_hours: training hours completed
target: 0 – Not looking for job change, 1 – Looking for a job change
Inspiration Predict the probability of a candidate will work for the company Interpret model(s) such a way that illustrate which features affect candidate decision.

CharlesXiao
- 粉丝: 22
最新资源
- 工程项目管理工作存在的问题及优化策略(1).docx
- 大数据在电力设计企业信息化建设的应用探讨.docx
- 多层电梯PLC07级电气自动化(PLC方向)二班.doc
- 互联网+在中职德育主题班会中的实践与研究.docx
- 计算科学导论学科论文的论文-计算机理论论文.docx
- 大型工程网络计划技术的应用复杂性研究.docx
- 《动态网站设计》html试题-答案.doc
- VC程序设计方案复习试题出试卷用.doc
- 客房管理系统-Visual-C++-6.0.doc
- 泵站运行调度中的计算机技术.docx
- 大数据背景下城建档案社会化服务作用体现的策略.docx
- 旅游电子商务的网站.docx
- 汇编语言-汇编语言资源
- 《中国网址》项目管理方案.doc
- 通信传输中光交换技术的关键技术原理和应用.docx
- 电气工程及其自动化的智能化技术微探.docx
资源上传下载、课程学习等过程中有任何疑问或建议,欢迎提出宝贵意见哦~我们会及时处理!
点击此处反馈


