Charles C Barnes
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  • Exploratory risk analysis dashboard
  • Supervised classification machine learning
  • Predicting ICU need during the COVID-19 pandemic

Portfolio

portfolio

Exploratory risk analysis dashboard

I used Power BI to explore how national workplace risk statistics vary depending on inspection program and US region. I found that state programs and the US West associated with safer working environments in 2012.

Title: 2012 National Workplace risk data

Links:

  • description | GitHub

  • demo | R Shiny app

Topics:

Exploratory analysis | Risk analysis | Dashboards

Software:

Power BI | R | Shiny | Quarto


Supervised classification machine learning

I used Python to build supervised classification machine learning models with the bank marketing dataset to classify whether a client will subscribe a term account. I progressed three different model types through optimization techniques and deployed a best-performing model.

Title: Classifying term subscription with client banking data

Links:

  • description & notebook | GitHub

  • deployed model (demo) | R Shiny app

Topics:

Supervised classification | Preprocessing | Modeling

Software:

Python | R | Shiny | Quarto

Model deployment example

Predicting ICU need during the COVID-19 pandemic

I used Python modules (sklearn, pandas, numpy) to conduct EDA of the COVID-19 ICU dataset and build predictive models to classify whether a person seeking treatment for COVID will require the ICU. I found that a random forest classifier had the best classification performance with an accuracy near 92%.

Links:

notebook | GitHub

Topics:

Supervised classification | Preprocessing | Modeling

Software:

Python | R | Quarto

 
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