I have a collection of industry-report spreadsheets and I need them turned into a reliable, easy-to-update predictive model that tells me where the market is heading next. The goal is clear: use AI / machine-learning techniques to uncover patterns in the data and generate forward-looking trend projections. Here is what I’m after: • Clean and preprocess the Excel files so the data is analysis-ready (handle missing values, standardise formats, merge relevant sheets). • Build and train a predictive model focused on market-trend forecasting; feel free to choose the most suitable approach (e.g., time-series algorithms, gradient boosting, or a lightweight neural network) as long as it can be retrained with new data. • Provide clear visual outputs—charts, graphs, or a small dashboard—that highlight key drivers and display the forecast over selectable time horizons. • Deliver everything in an accessible format: a commented Python notebook (or equivalent script), the final model file, and a concise summary slide or PDF explaining methodology, accuracy metrics, and how to rerun the pipeline on fresh reports. Industry-specific terminology is already embedded in the spreadsheets, so no external data gathering is required. If you have experience with tools like pandas, scikit-learn, TensorFlow, or Prophet, you’ll feel right at home. Accuracy, interpretability, and straightforward hand-off documentation are my priorities. If this sounds like a fit, I’m ready to get started.