A Data science and Analytics project with the main aim of doing some Descriptive and Exploratory Data Analysis and then applying predictive modelling for predicting why and which are the best and most experienced employees leaving prematurely?

This repository demonstrates how data science can help to identify the employee attrition which is part of Human Resource Management

People analytics project in R that implements predictive modeling to identify employees most likely to leave a company. Discussion around implications for the sample firm and proposed interventions draw on best practices in organizational development.

A Human Resource Analytics project that addresses the question "Why do employees leave?". Also helps us better understand factors for employee satisfaction

This repository contains the files necessary to build my free ebook called "R for HR: An Introduction to Human Resource Analytics Using R".

Healthcare Sector Employee Attrition Exploratory Data Analysis ## Introduction In this notebook we are going to apply an Exploratory Data Analysis (EDA) to the Watson Health Care employees dataset. The dataset contains employee and company data useful for supervised ML, unsupervised ML, and analytics. The main scope of the EDA is to analyse and…

This repository contains the files necessary to build my free ebook called "Python for HR: An Introduction to Human Resource Analytics Using Python".

Based on employee data recorded during 16 years of activity, a company seeks to reduce turnover rate, absences, and employee dissatisfaction; and increase performance.

Crawl information from github in friendly manner.

Utilize o Watson para otimizar analise de currículos e descobrir sua área de vocação

HR Dashboard Project using Tableau to visualize key HR metrics, demographics, and salary insights. The project simulates real-world HR data analysis, providing high-level overviews and detailed employee records for better decision-making.

This project analyzes employee attrition at Salifort Motors using machine learning and data analytics to identify key turnover drivers. The analysis spans data cleaning, exploratory data analysis (EDA), predictive modeling (logistic regression, decision trees, random forest, and XGBoost), and actionable HR recommendations.

Análises de RH analytics e BI realizada

This repo contains my HR Analytics project to predict employee attrition using an IBM dataset.