Featured Projects
Research, applications and modelling work presented as clear, on-site reports, including results that worked, results that did not and what each project taught me.
Bitcoin NLP × Volatility
An end-to-end natural-language-processing study that maps Bitcoin discussion themes, measures daily sentiment and tests whether social signals improve next-day volatility forecasts.
View reportChampion model XGBoost
Navigation-App Churn
A full churn-analysis case study using behavioural data, statistical testing, feature engineering and interpretable model comparison to assess which users may disengage.
View reportNYC Taxi Analytics
A multi-stage analytics project that moves from trip-level exploration and hypothesis testing to fare regression and tree-based classification on New York City taxi data.
View reportClean My Data
A Streamlit application that identifies common data-quality problems, supports cleaning decisions and produces a clear exploratory overview of uploaded datasets.
View reportFear Patterns with CCA
A canonical correlation analysis of how a seven-item computer-fear profile relates to an eight-item statistics-fear profile across 2,571 respondents.
View reportFinal test comparison
Insurance Claim Counts
An exposure-aware comparison of Poisson-family GLMs and XGBoost for insurance claim frequency, with validation-led selection, DHARMa diagnostics, calibration and explainability.
View reportBitcoin Volatility Forecasting
A validation-led study comparing econometric, machine-learning, neural-network and hybrid models for daily Bitcoin variance forecasting from 2015 to 2026.
View reportMultiple Imputation
A missing-data study using NHANES observations, chained equations and pooled uncertainty to compare BMI and cholesterol across Pre- and Post-COVID periods.
View reportBayesian Network MPG
A Bayesian-network study comparing an expert-defined vehicle dependency graph with a BIC-learned structure, then using conditional probability tables for MPG inference and classification.
View report