https://github.com/zescalante/data1030-final-project

Final project for DATA1030
https://github.com/zescalante/data1030-final-project

data-science machine-learning scikit-learn

Last synced: 7 days ago
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Final project for DATA1030

• Host: GitHub
• URL: https://github.com/zescalante/data1030-final-project
• Owner: Zescalante
• Created: 2024-10-01T18:39:40.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2024-10-23T19:43:48.000Z (14 days ago)
• Last Synced: 2024-10-25T14:31:08.841Z (12 days ago)
• Topics: data-science, machine-learning, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 2.74 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Binary Classification in a Galaxy Cluster Field Using Machine Learning

Fall 2024 - DATA 1030 - Final Project

_Author: Zacharias Escalante_

This project entails analyzing a catalog of source information contained in the field of the Abell 3266 galaxy cluster field, created using data from the LoVoCCS survey and other external surveys. Exploratory data analysis is first carried out, followed by the engineering of new features, as well as data splitting and preprocessing in preparation for passing into a machine learing pipeline.

## Contents

`Galaxies_Binary_Classif.ipynb`: Jupyter notebook containing data analysis (EDA, Splitting, Preprocessing).

`data_description.txt`: A Brief summary of columns (features) in the dataset.

`DATA_1030_Midterm_Presentation.pdf`: Midterm presentation slides explaining origin of dataset, EDA splitting, and preprocessing.