I need a solid predictive-modeling solution to forecast a key metric in my spreadsheet data. The raw information lives in Excel, but I’m comfortable with you exporting it into Python (Pandas, scikit-learn) to build a reliable regression model and then sending results back to Excel for easy use. Scope • Clean and prepare the Excel dataset, handling missing values and outliers. • Select and train the most suitable regression algorithms, compare performance, and fine-tune hyperparameters. • Deliver an annotated Python notebook (or .py script) plus an updated Excel file that includes predicted outputs and any helper formulas. • Provide a concise model-performance summary—R², MAE, and residual plots—so I can quickly gauge accuracy. • Wrap up with a short hand-off note explaining how to refresh the model when new rows are added. I’m after clear, actionable insights rather than academic theory, so keep the code readable and the explanations business-friendly.