Project Hub

OmniFeedback AI

Enterprise feedback ingestion, escalation triage, and a GenAI resolution copilot — with a live naive-vs-hardened overfitting demo built into the app.

🎤 Presentation: the code, slide by slide
15 slides with real code, line-linked to GitHub: data, star schema + ACID, ML, deep learning, evaluation, GenAI
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📚 Theory sheet
Every concept explained, with full forms, history, shortcomings and where it appears in the code
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📊 15-Slide Technical Walkthrough
Architecture, algorithms, the V1/V2 story, and real data insights
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🚀 Live Application
The full running Streamlit dashboard
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💻 GitHub Repository
Full source code, tests, and Dockerfile
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📄 Research Paper
Detecting and correcting synthetic-data overfitting — full methodology and results
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🔍 QA & Product Review
User journeys, QA findings, honest business-value framing
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🗓️ 21-Day Content Calendar
Screenshot-ready visuals + ready-to-paste LinkedIn posts and tweets
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📈 Data Insights
Confusion matrix, threshold sensitivity, error analysis
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🧭 Enhancement Roadmap
What's next, ranked by cost vs. leverage
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🏭 Production Readiness
What would need to change to run this as real infrastructure
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📓 Build Log
Every bug, fix, and modeling decision, written as it happened
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