AI-powered threat modeling that turns architecture diagrams into actionable risks
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Updated
Jan 19, 2026 - Python
AI-powered threat modeling that turns architecture diagrams into actionable risks
Predicting the default customers
Building an PD, LGD and EAD Model for Financial Modeling.
Portfolio of course work for my Master's in Data Science.
To provide complete workflow from Inferential Analytics, Predictive Analytics, Prescriptive Analytics and Evaluate the performance of prescriptions
Build a predictive model to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.
Housing price drivers with OLS + regularization + causal baseline; robust diagnostics. Python, scikit-learn, CI.
Machine Learning Project to understand the lifecycle metrics of a loan in order to minimize delinquent loans
Collection of data science projects demonstrating machine learning and analytics skills
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End-to-end credit default risk prediction system with Explainable AI (SHAP), Flask web app, animated risk gauge, batch prediction, and admin dashboard UI.
Reproducible OHLCV pipeline: baselines + SARIMAX/Prophet, uncertainty & drawdowns. Python, statsmodels, CI.
Streamlit legal ops automation: ETL + KPI dashboard (matters, utilization, AR aging, deadlines). Python, Pandas, SQL, CI.
Python-based enterprise risk intelligence engine for log analysis, anomaly detection, KRI-driven scoring, and automated narrative risk reporting. Designed for SMEs, cybersecurity teams, and governance functions. Built as applied AI technical evidence for the UK Global Talent route. Led by Ibrahim Akinyera.
Credit Risk analysis and predictive modelling of the German credit dataset. This repository holds all the R-scripts and markdown files for my report on the same
Real-return analysis across inflation episodes with bootstrapped CIs and allocation sketches. Python, Pandas, CI.
Studio green-light model: TMDB/OMDb pipeline, classification/quantile, decision rubric. Python, scikit-learn, CI.
An interactive Power BI project designed to help executives, procurement, logistics, finance, and risk teams monitor supply chain risks, delays, and cost impacts while enabling scenario planning for resilience.
Streamlit-based tool for mutual fund analytics with CAGR, Sharpe/Sortino, drawdowns, CAPM, Prophet forecasting, fund scoring, and K-Means clustering for benchmarking.
Deep-dive credit card fraud detection project focusing on extreme class imbalance, precision-recall metrics, threshold tuning, and business cost trade-offs.
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