I have a structured data set that must be turned into actionable forecasts as quickly as possible. Your task is to design, train, and validate an AI-driven model focused purely on data analysis and prediction. I’m open to the stack you prefer—Python with scikit-learn, TensorFlow, PyTorch, or another proven framework—as long as the final solution is reproducible and easy for me to run. Speed is critical: I’d like to see an initial proof-of-concept in the next few days and a polished, production-ready model shortly after. Alongside the code, I’ll need a concise read-me that explains preprocessing steps, chosen algorithms, hyper-parameter choices, and how to retrain the model when new data arrives. When you reply, highlight past work that demonstrates you have built and deployed predictive models before. Links, performance metrics, or short case studies are far more useful to me than a general résumé. Deliverables • Clean, well-commented source code and dependencies file • Trained model (or clear instructions to reproduce it) • Brief documentation covering setup, usage, and retraining steps If you can jump in immediately and hit those milestones, I’m ready to award the project today.