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mickeywmoore/README.md

Mickey Moore

AI & ML Specialist | Python | Prompt Engineering he/him

💻 Technical Stack

  • Languages: Python, SQL (Advanced)
  • Machine Learning: TensorFlow, Keras, Scikit-learn, XGBoost, CatBoost
  • Data Engineering: Pandas, Selenium, SQLite, Automation Pipelines
  • Environment: Linux, Git, Jupyter
  • Security & Bug Bounty: Web Application Security, API Logic Flaws, Custom Reconnaissance Automation, Burp Suite, Kali Linux

🔗 Connect

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  1. Retail-360-Customer-Lifecycle-Engine Retail-360-Customer-Lifecycle-Engine Public

    Full-stack Data Science engine: Advanced SQL feature engineering, Customer Segmentation (K-Means), and LTV Prediction using Deep Learning (TensorFlow). Includes automated AI Ethics & Bias auditing.

    Jupyter Notebook

  2. customer-churn-prediction-model customer-churn-prediction-model Public

    A machine learning model (Logistic Regression) to predict Telco customer churn, built with Python, Pandas, and Scikit-learn.

    Jupyter Notebook

  3. pandas-data-cleaning-project pandas-data-cleaning-project Public

    A Python script demonstrating a data cleaning workflow with the Pandas library.

    Python

  4. csv-deduplicator-notebook csv-deduplicator-notebook Public

    A Jupyter Notebook that reads a CSV, removes duplicate entries using Pandas, and saves the clean data. (Skills: Python, Pandas, Data Cleaning)

    Jupyter Notebook

  5. university-admissions-model university-admissions-model Public

    A Python project implementing a Logistic Regression model to predict university admissions. (Skills: Python, Scikit-learn, Machine Learning)

    Python

  6. mario-kart-analysis mario-kart-analysis Public

    A Python project demonstrating data aggregation and dictionary manipulation by analyzing Mario Kart race results. (Skills: Python, Data Analysis)

    Python