This repository contains a data analysis project focused on predicting income categories using classification algorithms. The project was completed as part of a university course and aims to showcase data analysis, machine learning modeling, and presentation skills.
- Objective: Predict income categories based on various features using classification algorithms.
- Data: Utilized a dataset containing information about individuals and their income levels.
- Approach: Explored different classification algorithms, including Logistic Regression, Random Forest, and Decision Trees.
- Highlights: Explored data preprocessing, feature engineering, hyperparameter tuning, and model evaluation.
- Key Results: Successfully built and compared multiple models, with certain cases where the Decision Tree outperformed Random Forest.
notebooks/: Jupyter notebooks containing the project code, analysis, and model implementations.data/: Datasets used for training and testing the models.images/: Visualizations and charts generated during the analysis.report/: Detailed project report summarizing the approach, findings, and results.