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Practical Guide to Applied Conformal Prediction in Python : Learn and Apply the Best Uncertainty Frameworks to Your Industry Applications by Valeriy Manokhin is a nonfiction available to read on EtoBox.

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Valery Manokhin, Agus Sudjianto, "Practical Guide to Applied Conformal Prediction in Python: Learn and Apply the Best Uncertainty Frameworks to Your Industry Applications" Take your machine learning skills to the next level by mastering the best framework for uncertainty quantification - Conformal Prediction Book Description In the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. "Practical Guide to Applied Conformal Prediction in Python" addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework set to revolutionize uncertainty management in various ML applications. Embark on a comprehensive journey through Conformal Prediction, exploring its fundamentals and practical applications in binary classification, regression, time series forecasting, imbalanced data, computer vision, and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse indust

Who reads Practical Guide to Applied Conformal Prediction in Python : Learn and Apply the Best Uncertainty Frameworks to Your Industry Applications?

Author

Valeriy Manokhin

Publisher

Packt Publishing, Limited

Published

2024

Language

EN

ISBN

9781805120919

Category

nonfiction

Subjects

Computer Science, Mathematics, Science