I built a comprehensive sales tracking spreadsheet for an engine oil business that automatically tracks daily sales, calculates profit per transaction and labels each sales. The client can instantly see their most profitable product, total revenue, total costs and net profit for any period without any manual calculations.

This is exactly the kind of clarity every small business owner needs — being able to see profit per transaction and top products at a glance without manual calculations is a game changer. Great work on the performance labelling too! 🙌

For a Predictive Analytics test model, I built two predictive models for clinical outcomes: a logistic regression classifier diagnosing tumours as malignant/benign (89.5% accuracy, 0.97 AUC) on the Breast Cancer Wisconsin dataset, and a multiple linear regression model predicting diabetes disease progression (R² = 0.49) from BMI, blood pressure, and cholesterol markers. Covered the full pipeline: EDA, multicollinearity diagnostics, train/test splitting, feature scaling, model evaluation, and individual patient-level predictions with clinical interpretation