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Machine Learning Analysis Work

Overview

This repository contains a comprehensive study on machine learning, focusing on various models implemented using Python. The analysis delves into data exploration, variable analysis, and model evaluation. The work was conducted in Spanish as it was part of a course conducted in that language.

Project Structure

The repository is organized as follows:

  • Data Analysis: Initial exploration and analysis of the dataset, including an in-depth examination of variables.

  • Models:

    • Naive Bayes: Implementation and analysis of Naive Bayes model.
    • Neural Networks: Exploration and evaluation of neural network models.
    • Unsupervised Learning: Study of unsupervised learning techniques and their applications.
    • Ensembles (Variation-based): Implementation and assessment of ensemble models based on data variation.
    • Ensembles (Decomposition-based): Analysis and implementation of ensemble models based on data decomposition.

Contributors

  • Unai Gurbindo

Feel free to contribute by opening issues, providing suggestions, or submitting pull requests.

Note: This README is in English for wider accessibility, but the actual project and code are in Spanish.

Enjoy exploring the fascinating world of machine learning!

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