Predicting Stars, Galaxies, and Quasars with ML

Welcome to "Predicting Stars, Galaxies, and Quasars with ML", a project where the realms of astronomy and machine learning intersect to create a unique and compelling experience.

About This Project

Are you fascinated by the universe and the treasures it holds? This project brings these two worlds together by applying machine learning techniques to classify cosmic bodies such as stars, galaxies, and quasars using the data set Sloan Digital Sky Survey DR14.

Project Overview

Foundational Astronomy

• Astronomical Basics: Understand the characteristics of different celestial objects essential for working with astronomical data.

Data Handling Skills

• Data Preprocessing: cleaning , manipulating , and preprocessing datasets typical of astronomical data collection efforts.

Machine Learning Techniques

• Algorithm Mastery: Diving into machine learning algorithms and training to categorize vast and complex cosmic datasets.

Model Evaluation

• Performance Validation: techniques for validating the performance of your machine learning models, ensuring accurate and reliable classification results.

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Project Outline

Introduction

• Overview of astronomy and machine learning
• Introduction to the project structure and objectives

Foundational Astronomy

• Basic concepts of astronomy
• Characteristics and classifications of stars, galaxies, and quasars

Data Handling

• Sources of astronomical data
• Techniques for data cleaning and preprocessing
• Handling large datasets

Machine Learning Techniques

• Introduction to machine learning algorithms -Decision tree classifier -Linear Regression Classsifier -KNN Classifier

Model Evaluation

• Techniques for evaluating model performance
• Cross-validation and hyperparameter tuning
• Interpreting model results

uncover the secrets of the universe with the power of machine learning!