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Define the Objective: Clarify the goal of the prediction, whether it forecasting sales, predicting customer churn, or identifying fraud.
Prepare Data: Collect, clean, and transform data to ensure it ready for modeling.
Select Model Type: Choose between Power BI native tools, Azure ML integration, or custom scripts, depending on the complexity of the analysis.
Train and Test: Use a portion of the data to train the model and reserve a set for testing to evaluate performance.
Refine Model: Adjust parameters, perform feature engineering, or try different algorithms to improve accuracy.
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