This project is part of the Udacity Machine Learning Engineer Nanodegree program and aims to build a model that can predict whether an individual's income is above or below $50,000, so that a charity organization can focus its efforts on people who are more likely to donate. The project involves data exploration and preprocessing, feature engineering and selection, and evaluation of various supervised machine learning models.

To run this project, you will need Python 3.x with the following libraries:

• numpy
• pandas
• matplotlib
• seaborn
• scikit-learn

You can install these libraries using pip by running:

pip install numpy pandas matplotlib seaborn scikit-learn

Alternatively, you can install Anaconda, a pre-packaged Python distribution that contains all the necessary libraries and tools for this project.

You can open the Jupyter notebook finding_donors.ipynb to see the code and results of this project. You can run the notebook cell by cell, or you can restart and run all cells to reproduce the results.

The notebook contains detailed explanations and comments for each step of the project, as well as questions that you need to answer to demonstrate your understanding of the concepts.

The contents of this repository are covered under the MIT License.

The dataset used in this project is from the UCI Machine Learning Repository. The project instructions and starter code are provided by the Udacity Machine Learning Engineer Nanodegree program.