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Mastering Forecasting Metrics & Accuracy: For Data Science and Beyond

Valery Manokhin

Mastering Forecasting Metrics & Accuracy: For Data Science and Beyond

Forecasting models are only as good as the metrics used to measure them. Yet many teams still rely on outdated or misleading measures like MAPE. This book is the first comprehensive, practitioner-friendly guide dedicated entirely to forecast evaluation metrics — blending clear theory, Python recipes, and real-world case studies.

Learn how to avoid common pitfalls, measure bias, handle intermittent demand, and apply advanced metrics like MASE, RMSSE, CRPS, pinball loss, and calibration scores. Each chapter includes formulas, code, and visuals to make concepts easy to apply.

Perfect for data scientists, ML engineers, analysts, researchers, and industry professionals in retail, finance, and energy. No heavy math required.

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Measure what matters.

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About the Book

Mastering Forecasting Metrics & Accuracy: For Data Science and Beyond

Forecasting models are only as good as the metrics used to measure them. Yet many teams still rely on outdated or misleading measures like MAPE. This book is the first comprehensive, practitioner-friendly guide dedicated entirely to forecast evaluation metrics — blending clear theory, Python recipes, and real-world case studies.

Learn how to avoid common pitfalls, measure bias, handle intermittent demand, and apply advanced metrics like MASE, RMSSE, CRPS, pinball loss, and calibration scores. Each chapter includes formulas, code, and visuals to make concepts easy to apply.

Perfect for data scientists, ML engineers, analysts, researchers, and industry professionals in retail, finance, and energy. No heavy math required.

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PythonComputer ScienceData ScienceDeep LearningEngineeringEducationMachine LearningNeural Networks

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About the Author

Valery Manokhin

Dr Valeriy Manokhin, MBA, CQF

ML expert and 7× book author building real-world forecasting systems

Dr. Valeriy Manokhin is a machine learning expert with a PhD in ML and significant experience designing enterprise-grade forecasting systems for Fortune 500 companies and fast-growing startups.

He is the author of 7 books on forecasting and conformal prediction, including Mastering Modern Time Series Forecasting and Applied Conformal Prediction, widely used by practitioners worldwide. His work bridges rigorous research with real-world execution.

Dr. Manokhin has built forecasting systems supporting multimillion-dollar decisions across finance, energy, industrial, and technology sectors. His approach focuses on reliable, scalable forecasting systems that work in production and deliver measurable business impact.

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