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Description

In the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. The book addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework to manage uncertainty in various ML applications. Learn how Conformal Prediction excels in calibrating classification models, produces well-calibrated prediction intervals for regression, and resolves challenges in time series forecasting and imbalanced data. Discover specialised applications of conformal prediction in cutting-edge domains like 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 industries. With practical examples in Python using real-world datasets, expert insights, and open-source library applications, you will gain a solid understanding of this modern framework for uncertainty quantification. By the end of this book, you will be able to master Conformal Prediction in Python with a blend of theory and practical application, enabling you to confidently apply this powerful framework to quantify uncertainty in diverse fields.

What you will learn

The fundamental concepts and principles of conformal prediction

Learn how conformal prediction differs from traditional ML methods

Apply real-world examples to your own industry applications

Explore advanced topics - imbalanced data and multi-class CP

Dive into the details of the conformal prediction framework

Boost your career as a data scientist, ML engineer, or researcher

Learn to apply conformal prediction to forecasting and NLP

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

AI Assistant (beta) to help accelerate your learning

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Practical Guide to Applied Conformal Prediction in Python: Learn and apply the best uncertainty frameworks to your industry applications

What do you get with eBook?