Predicting Employee Productivity Using Tree Models

In this project, you'll assume the role of a data scientist working with a garment factory dataset to predict employee productivity. Using Python and the scikit-learn library, you'll clean the data, build a decision tree model, evaluate its performance, and explain the results to a non-technical audience. This project allows you to showcase your skills in data preparation, machine learning modeling with decision trees and random forests, and communicating data-driven insights. You'll develop a robust model to identify the key factors driving productivity, providing actionable recommendations to improve factory operations. Objective: Leverage decision tree and random forest algorithms to predict garment worker productivity and deliver insights to guide factory enhancements.