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Prodoorknob/README.md

Applied Data Science graduate student focusing on sports analytics, large-scale public datasets, and interactive data applications.

Interests:

  • Sports analytics (Cricket, NFL, Formula One)
  • Data visualization & storytelling
  • Scalable data pipelines

Key technologies:

  • Python (pandas, NumPy, scikit-learn)
  • Data visualization (Plotly, Dash, Matplotlib)
  • Applied analytics & metric design
  • Public and sports datasets (USDA, NFL tracking, cricket ball-by-ball)
  • Lightweight deployment (Streamlit, Dash)

Selected work:

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  1. Big_Data_Bowl Big_Data_Bowl Public

    True Speed, a proprietary metric derived from the Big Data Bowl 2026 tracking data.

    Jupyter Notebook

  2. Intent_Quotinet_Cricket Intent_Quotinet_Cricket Public

    Intent Quotient (IQ) : Cricket Batting Intent Analysis

    Jupyter Notebook

  3. FormulaOne_Analysis FormulaOne_Analysis Public

    Machine learning Model to predict Formula One race winner based on previous data.

    Jupyter Notebook 1

  4. Agricultural_Data_Analysis Agricultural_Data_Analysis Public

    USDA Survey Statistics: Understanding farming one stat at a time.

    Python

  5. DSMLIUI/Pyspark-workshop DSMLIUI/Pyspark-workshop Public

    Pyspark workshop

    Jupyter Notebook 1 2

  6. grantstarnes/h501-group6 grantstarnes/h501-group6 Public

    This is our video games data project for INFO-H501

    Jupyter Notebook 1