This ebook explores how organizations can improve predictive accuracy by combining machine learning with interactive visualization. It explains why traditional “black box” forecasting often fails to gain trust and how visual data science enables transparency, explainability, and validation. The ebook covers forecasting fundamentals, model evaluation, and scenario testing while emphasizing human-in-the-loop analytics. Real-world examples show how teams use visual exploration to compare models, identify bias, and understand uncertainty. The result is more reliable predictions that business users can trust and confidently use to guide strategic decisions.

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