Ensemble-Learning-Notebooks

This repository contains a collection of Jupyter notebooks each covering different ensemble learning methods. We then tackle several datasets using these methods and evaluate the results. Many of the notebooks get under the hood and break down several of these ensemble learning methods.

Notebook Categories

The following notebooks can be found in the notebooks/ directory:

• voting_and_stacking.ipynb: Covers Voting Classifier and Stacking ensemble learning methods.
• bagging_and_pasting.ipynb: Covers Bagging and Pasting ensemble learning methods.
• random_forests.ipynb: Covers Random Forests, a popular ensemble learning method.
• boosting.ipynb: Covers Boosting ensemble learning method.

Getting Started

1. Clone the repository to your local machine:

   git clone https://github.com/Zane-dev16/Ensemble-Learning-Notebooks.git

2. Run the notebooks in your preferred order on any compatible platform

Bibliography

• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (3rd Edition) by Aurélien Géron