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Can I read Practical Guide to Applied Conformal Prediction in Python : Learn and Apply the Best Uncertainty Frameworks to Your Industry Applications on EtoBox?

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.

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

Take your machine learning skills to the next level by mastering the best framework for uncertainty quantification - Conformal Prediction Key Features Master Conformal Prediction, a fast-growing ML framework, with Python applications. Explore cutting-edge methods to measure and manage uncertainty in industry applications. The book will explain how Conformal Prediction differs from traditional machine learning. 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-cl

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

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Valeriy Manokhin
Publisher
Packt Publishing, Limited
Published
2023
Language
EN
ISBN
9781805122760
Category
nonfiction
Subjects
Mathematics, Computer Science, Science

Other editions & translations

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