Finding Donors 💰

Description 📝

This project is a machine learning project classification problem aims to find the donors who donate with more than 50K. The charity is called MLCharity and it uses the demographic data about the donors.

Approach

There are three models used to train the data. They are:

• Decision Trees.
• Gradient Boosting (Ensemble Methods).
• Support Vector Machine (SVM).

By Comparing the three models, Gradient Boosting classifier was the best model according to the test F1-score and accuracy.

Getting Started 🚀

Prerequisites

1. Download and Install Python.
2. Install Jupyter Notebook.
3. Install the following libraries: NumPy, Pandas, sci-kit learn, and matplotlib. Or you can download and install Anaconda and install the needed libraries directly.

Starting with the project

1. Clone the repo with: git clone https://github.com/ReemAyman/Finding-Donors.git.
2. Go through the finding_donors.ipynb noteboook for further details about the project by using the command jupyter notebook in the project directory.

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Disclaimer ⚠️

This project is licenced from the Udacity's Machine Learning Cross-skilling Track Nanodegree Program. It can only be used for learning and referencing purposes.

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