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harrystaley/README.md

Harry πŸ‘‹

Software Engineer | OMSCS (AI Track)
Cybersecurity β€’ Python Automation β€’ Applied Machine Learning

Engineer with a background in security and defense systems, currently focused on applying machine learning to real-world operational problems. I’m building AI capabilities on top of practical experience in automation, data processing, and reproducible system design.

My work sits at the intersection of:

  • Machine learning workflows
  • Security data analysis
  • Python-based automation
  • Operationally grounded system design

🎯 Current Focus

  • Applied machine learning fundamentals
  • Building reproducible AI workflows
  • Model evaluation and validation
  • Data preprocessing and feature engineering
  • Applying ML techniques to security and operational datasets

πŸš€ Selected Projects

πŸ” Cybersecurity Honeypot Lab

Practical security lab environment for traffic capture and analysis.

  • Infrastructure-as-code deployment
  • Data collection suitable for anomaly detection workflows
  • Reproducible security experimentation environment

πŸ“Š Defense Data Automation

Python tooling for extracting and transforming structured defense personnel data.

  • Data normalization and preprocessing pipelines
  • Automation of manual reporting workflows
  • Structured datasets suitable for analytics and ML experimentation

πŸŽ“ Open-Source Teaching Materials

Course resources and structured learning content for cybersecurity education.

  • Hands-on lab environments
  • Python scripting exercises
  • Applied systems thinking

🧠 What I'm Learning (AI)

  • Supervised learning workflows
  • Feature engineering techniques
  • Model evaluation strategies
  • Practical ML experimentation
  • Integrating AI into existing engineering workflows

πŸ›  Technical Background

Languages: Python, Bash, SQL

Data & ML:

  • Pandas
  • Data preprocessing workflows
  • Experimentation and evaluation pipelines

Security:

  • Network labs
  • Defensive tooling
  • Infrastructure experimentation

Tools:
Linux β€’ Git β€’ Cloud environments


βš™οΈ Engineering Approach

  • Prefer simple, maintainable solutions
  • Automation where possible
  • Practical experimentation over theoretical complexity
  • Learning through building and iteration

πŸ“ˆ Current Work

  • OMSCS Artificial Intelligence track
  • Building AI-focused portfolio projects
  • Integrating ML techniques into security workflows

Pinned Loading

  1. open-source-data-science-degree-python open-source-data-science-degree-python Public

    A fully curated, open-source Data Science curriculum focused on Python. Includes top-tier university courses (MIT, Stanford, Princeton) covering essential topics in computer science, data analysis,…

    22 5

  2. OMSCS-Anki OMSCS-Anki Public

    Forked from wyohm/OMSCS-Anki

    A collaborative repository for enhancing and sharing Anki study materials tailored to courses in the Georgia Tech OMSCS program. Contribute to improve the decks or download them via AnkiWeb or usin…

    16 1

  3. DataCamp DataCamp Public

    A collection of Jupyter notebooks showcasing my progress and completion of data science coursework on DataCamp, featuring exploratory data analysis and Python-based projects. Note: These materials …

    Jupyter Notebook 6

  4. Contract_Name_From_Defense.gov Contract_Name_From_Defense.gov Public

    A Python script for web scraping and extracting award descriptions from the DoD contract awards news site, outputting the data into an Excel worksheet. Ideal for data scientists and developers inte…

    Python 5

  5. Open-Source-Cybersecurity-Degree Open-Source-Cybersecurity-Degree Public

    A comprehensive, open-source pathway to a cybersecurity career utilizing free, high-quality resources from prestigious institutions like MIT and Stanford, with a focus on technical skills and Pytho…

    4

  6. Techtonica/techtonica.org Techtonica/techtonica.org Public

    This repo is for the techtonica.org website for Techtonica, a nonprofit tech training program that helps women and non-binary adults with low incomes overcome barriers into tech careers.

    HTML 37 70