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Machine Learning Projects (GMU Summer Camp)

This repository is a collection of machine learning projects completed during a summer camp at George Mason University. Each folder contains a different experiment or learning module focused on core ML concepts, algorithms, and data processing techniques.

The projects were developed hands-on as part of the camp curriculum, exploring topics like supervised learning, natural language processing, neural networks, genetic algorithms, and more.


📁 Project Structure

Folder Description
DataScraping Scripts for scraping and collecting datasets from online sources.
dataCleaning Preprocessing scripts for cleaning, formatting, and structuring raw data.
GeneticAlgorithm Implementation of a basic genetic algorithm for optimization tasks.
NLTK Natural Language Toolkit examples for text analysis and NLP tasks.
RandomForrestML Random Forest classification/regression experiments.
SVMClassification Support Vector Machine models applied to classification datasets.
blasterNN A simple neural network project (possibly a game or classifier—see inside).

📌 About the Camp

  • Location: George Mason University - Online
  • Duration: Summer (4 years ago)
  • Focus Areas: Machine Learning fundamentals, Python programming, algorithms, and applied AI techniques.

About

This repository is a collection of machine learning projects completed during a summer camp at George Mason University. Each folder contains a different experiment or learning module focused on core ML concepts, algorithms, and data processing techniques.

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