Historical battle simulation package for Python

• UpdatedAug 19, 2020
• Python

This repository contains all the data related to the employee Attrition Prediction model

• UpdatedSep 9, 2017
• R

This repository contains a collection of Data Science and Machine learning projects.

• UpdatedSep 17, 2022
• Jupyter Notebook

Uncover the factors that lead to employee attrition using IBM Employee Data

• UpdatedJul 23, 2019
• Jupyter Notebook

A large company named XYZ, employs, at any given point of time, around 4000 employees. However, every year, around 15% of its employees leave the company and need to be replaced with the talent pool available in the job market. The management believes that this level of attrition (employees leaving, either on their own or because they got fired)…

• UpdatedNov 28, 2019
• Jupyter Notebook

Leverage external data and non-traditional methods to accurately assess and shortlist candidates with the relevant skillsets, experience and psycho-emotional traits, and match them with relevant job openings to drive operational efficiency and improve accuracy in the matching process

• UpdatedApr 21, 2021
• R

This repository contains an R functions designed to estimate the Average Treatment Effect on the Treated (ITT) and Local Average Treatment Effect (LATE) using various methods, including Difference in Means and Difference in Differences. The function allows for adjustment for clustering and provides options for methods such as Lee Bounds and IPW

• UpdatedAug 27, 2024
• R

Built a model using XGBoost that predicts the chances of Attrition of an employee working at IBM with 84% Precision.

• UpdatedFeb 29, 2020
• Jupyter Notebook

Uncover the factors that lead to employee attrition at IBM

• UpdatedOct 27, 2019
• Jupyter Notebook

A primer course on Data Science by Consulting & Analytics Club, IIT Guwahati

• UpdatedJun 22, 2020
• Jupyter Notebook

A flexible and powerful class for surgical removal of aged files and folders. Includes desktop configuration builder/manager, and a console app for human-free operation. Class can be directly included in an application.

• UpdatedMay 6, 2023
• C#

In this project I wanted to predict attrition based on employee data. The data is an artificial dataset from IBM data scientists. It contains data for 1470 employees. Te dataset contains the following information per employee:

• UpdatedMar 25, 2020
• Python

HR Data를 활용한 퇴사 예측 모델 구현 프로젝트입니다 📊 dashboard

• UpdatedMay 10, 2023
• Jupyter Notebook

• UpdatedSep 19, 2018
• Jupyter Notebook

Developed a comprehensive HR analytics dashboard to monitor employee attrition, performance, and engagement, utilizing metrics like job role, education, and work-life balance for data-driven decision-making.

• UpdatedAug 6, 2024

This repository contains a comprehensive study on employee attrition analysis using data mining techniques. It includes data preprocessing, visualization, and predictive modeling (with algorithms such as Decision Tree, Random Forest, and Logistic Regression) to identify key factors influencing attrition, using the IBM HR dataset.

• UpdatedDec 23, 2024
• Jupyter Notebook

Given the monthly information for a segment of employees for 2016 and 2017, predict whether a current employee will be leaving the organization in the upcoming two quarters (H1 2018)

• UpdatedNov 21, 2021
• Jupyter Notebook

NGO Fund Raising Attrition Churn Modelling

• UpdatedAug 30, 2019
• Jupyter Notebook

Analysis of employee attrition for the company and the variation by gender, department, job roles, level of education, field of education, age band, frequency of business travel, and marital status.

• UpdatedOct 3, 2024

What makes an employee stay and what makes him leave?

• UpdatedJul 11, 2017
• Jupyter Notebook