In this project I did Complete EDA, and Build a ML model that can accurately predict whether an Employee will be leave a company or not based on different factors.
The goal of this project is to analyze employee retention data to uncover insights that can help improve retention strategies. By identifying key factors that influence employee attrition, we aim to provide actionable recommendations for enhancing employee satisfaction and retention rates.
HR analytics project analyzing employee attrition across 1,470 employees using SQL, Python, and Tableau , logistic regression model, RFM-style segmentation, and identification of top at-risk employees.
Exploratory Data Analysis (EDA) of the IBM HR Analytics Employee Attrition dataset to identify key factors influencing employee attrition. The project includes data cleaning, statistical analysis, feature exploration, visualization, and business insights to understand employee turnover patterns and support data-driven HR decision-making
Analyzing employee attrition trends using MySQL & Power BI to improve workforce retention
This Power Bi dashboard analyzes employee attrition trends in a company. The key insights were visualized to help identify patterns affecting employee retention.
An HR analytics project exploring employee attrition using Python, data analysis, and a Dash dashboard.
Interactive HR Employee Attrition Dashboard using Power BI
Analysing the HR Analytics data using Power BI to gain insights of features affecting the attrition rate of employees by analyzing various features.
Power BI dashboard analyzing HR workforce trends, employee attrition, compensation, career progression, and employee experience.
Tableau Dashboards visualizing insights from various datasets.
Interactive Power BI dashboard analyzing employee attrition patterns across demographics, job roles, compensation, tenure and workforce factors.
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