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I’m looking for an expert who can build a reliable predictive AI model that works with time-series data. I have the raw datasets ready; what I need is the full modeling workflow—from exploratory analysis and feature engineering through training, validation, and clear performance reporting. Key objectives: • Choose the most suitable algorithms (e.g., ARIMA, Prophet, LSTM, or hybrids) and justify the selection. • Handle data preprocessing, missing-value treatment, and scaling so the model remains robust in production. • Deliver reproducible code (Python preferred, using frameworks such as TensorFlow, PyTorch, or scikit-learn) and concise documentation that explains setup, hyperparameters, and retraining steps. • Provide evaluation metrics like MAE, RMSE, and visual forecasts to make results easy to interpret. If you have experience deploying models, please mention it, as a follow-up phase may include packaging the solution behind an API. Let me know your relevant projects with time-series forecasting so I can gauge fit quickly.
Project ID: 40424199
3 proposals
Remote project
Active 11 days ago
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