Found 16 repositories(showing 16)
surajmalthumkar8
AI-Web-APP-HR-Absenteeism-Predictor
Ishan2924
Absenteeism Predictor using logisticRegression
matiasrodriguezc
Full-stack MLOps application that predicts employee absence hours. Built with Next.js (React), Python (FastAPI), and Scikit-learn, featuring a continuous training loop orchestrated by Apache Airflow.
hemanjalireddy
No description available
prithvimurjani
Given data of a company's employees regarding when they were absent from work, this implementation performs appropriate preprocessing and model building to find out how likely an employee is to be absent again.
Aneesh1829
Absenteeism Prediction
vjarwal
No description available
liyi54
A project for predicting staff absenteeism in companies
VnyC
Absenteeism probability predictor using scikit learn
Shubham01-T
Developed a Logistic Regression model to predict employee absenteeism, determining whether an employee will be absent from work based on various factors.
RubinaKafle
No description available
Deploying our Employee Absenteeism predictor on Heroku
MohanKumar2002
No description available
sree1975-cyber
No description available
HugoOrtega1
No description available
dlopezmaci001
The experimental data we are going to use is the Absenteeism at work Data Set (https://archive.ics.uci.edu/ml/datasets/Absenteeism+at+work). The first goal with this dataset is to decide what do you want to predict. You must determine what categorical variable to construct over the existing predictors, to classify/predict (binomial or multinomial) the absenteeism of individuals. Examples: • Binomial: Individuals with more than X hours in total (based on ’Absenteeism time in hours’ predictor), or less than that.
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