Pelarasan Model Jobs

I have a clean, ready-to-use dataset and now need a complete predictive analysis pipeline built around it. The job is straightforward: take my data, explore it, engineer the right features, train and tune an appropriate model, and hand back production-ready code that I can rerun whenever new records arrive. Python is my preferred language, and I’m comfortable with common libraries such as pandas, scikit-learn, XGBoost, TensorFlow or PyTorch—feel free to choose whichever stack best fits the problem once you’ve inspected the data. Please keep everything reproducible: a single script or notebook, a clear , and comments that explain why each step was taken. Acceptance criteria • End-to-end code executes without errors on my machine. • Model delivers a measurab...

I need a supervised learning model built from the ground up. You will take my raw data, handle preprocessing, select and justify the algorithm, train, tune, and deliver a production-ready model with accompanying Python code (TensorFlow, PyTorch, or scikit-learn are all acceptable). Your proposal should focus on your relevant experience with similar supervised learning projects—please highlight datasets you have tackled, algorithms you excel with, and any deployment or MLOps know-how. No lengthy sales pitches; I want to see evidence that you can translate business objectives into high-performing, explainable models. Deliverables • Clean, well-commented source code and notebooks • Reproducible training pipeline • Evaluation report covering accuracy and at least one...