- Full Portfolio: In-depth analysis, modeling, and diagnostics across the steel industry
susan-schnitzel-portfoli-jvjb3uo.gamma.site
Susan Schnitzel Portfolio of Analysis of Steel Industry
Key Concepts: Diagnostics, Seasonality, Humidity Regimes Modeling Pillars & Behavioral Themes Toolkit Behind the Analysis: Python , R, Power BI, Gamma App, Kaggle GitHub Source: “Steel Industry Energy and Emissions Data,” available on Kaggle Decoding Steel Plant Systems: Energy Use, Emissions,
- Condensed Portfolio: Streamlined highlights for quick review
condensed-portfolio-stee-s9q7vv7.gamma.site
Condensed_portfolio_steel_analysis_srschnitz
Curated Highlights from a 130+ Slide Portfolio in Predictive Diagnostics & Regime-Aware Modeling Key Insights: Energy, Emissions, and Optimization Optimizing Energy Use at DAEWOO Steel: A Data-Driven Approach Cornerstone initiative focused on 2018 operations at the Gwangyang plant. Achieved ~$20
- Machine Learning Addendum: CO₂ Modeling & Diagnostics
random-forest-classifica-ug96b3s.gamma.site
Random Forest Classification of CO2 ML
To complement my regression model, I applied classification to evaluate how different machine learning techniques interpret the same emissions signal. With an R² of 0.9998, the regression model captured CO₂ levels with near-perfect precision. The classifier didn’t replace it—it discretized the sam
- Pills, Claims, and Clustering -Semantic Signals and Healthcare Data Deep Dive( In Progress)
- Beds, Baths, and Binning: A Semantic Airbnb Deep Dive (In Progress)
