Popular GitHub Repositories for Employee Attrition

AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

The open source Solver AI for Java, Python and Kotlin to optimize scheduling and routing. Solve the vehicle routing problem, employee rostering, task assignment, maintenance scheduling and other planning problems.

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

Build autonomous AI agents for the Zero-Employee Enterprise (ZEE). Create intelligent, context-aware agents with unprecedented ease and functionality.

CollabChatbot is a cutting-edge, open-source project designed to revolutionize how organizations access employee information and foster team collaboration. This beta version introduces a suite of powerful features, including instant personal details, real-time occupancy updates, skill identification, and smart team-building recommendations

Employee Productivity GenAI Assistant Example is an innovative code sample and architecture pattern designed to enhance writing tasks efficiency using AWS serverless technologies and Amazon Bedrock's generative AI models.

The face recogntion system is used to train the faces of employees and detect them when they walk past the camera. It can be used as an attendence system for the employees.

Blockchain-powered supply chain management system with ML-driven sales prediction. Streamlines supplier-employee transactions and inventory management. Built with MERN stack, Solidity, and Flask.

End-to-end proof of concept showing core MLOps practices to develop, deploy and monitor a machine learning model for an employee retention workload using Databricks and Kubernetes on Microsoft Azure.

PTIT's Major Project: Website Programming - This repo contains a chatbot for a clothing store. The chatbot acts as an employee with specific knowledge about clothing consultation, website support, and store information.

毕业设计项目：在线员工管理系统

Developed an end-to-end machine learning solution for predicting employee churn using Azure Databricks, leveraging Spark for data processing, MLflow for managing the ML workflow, and deploying the model using Databricks model serving.

CRUD Operations and Text-Utils in Django

This project focus on building different machine learning models to make predictions on employee attrition and performance

A Deep Neural Network that can Classify Employee Churn with ~97% Accuracy

This project comprises of hybrid model of LBPH, CNN and frontal_haascade model. Frontal Haarcascade is used for face detection from the image, LBPH(Local Binany Pattern Histogram) is used for face recognition and CNN is used for face mask detection system. mySQL database is used to store the records of employee, which is used while recognizing face. Flask framework is used to build front-end.

A machine learning web app which predicts whether an employee gets promoted or not

Simple, in-memory Python tool to manage employee schedules and shifts, supporting weekly planning, shift registration, auto-logging based on weekly schedule, conflict detection, and report generation.

The GenAI Agentic HR Assistant is an AI-powered agentic application designed to streamline HR management tasks. This application leverages the power of MongoDB, LLMs, and agentic workflows to provide intelligent and efficient solutions for employee record management, team formation, and natural language query resolution.

This project was the outcome of the Corporate Reseach Project as a part of Masters in Data Sciences and Business Analytics program at ESSEC-CentraleSupelec and monitored by Deloitte. In this study, we propose and evaluate a predictive model for employee churn using machine learning techniques.