Practical Guide to Applied Conformal Prediction: Learn and apply the best uncertainty frameworks to your industry applications (English Edition)

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

Embark on an insightful journey with 'Practical Guide to Applied Conformal Prediction in Python', a comprehensive resource that equips you with the latest techniques to quantify uncertainty in machine learning and computer vision models effectively.

This book covers a wide array of real-world applications, including Conformal Prediction for forecasting, computer vision, and NLP, as well as advanced examples for handling imbalanced data and multi-class classification problems. These practical case studies will enable you to apply your newfound knowledge to various industry scenarios.

Designed for data scientists, analysts, machine learning engineers, and industry professionals, this book caters to different skill levels - making it an ideal resource for both beginners and experienced practitioners. Delve into the latest Conformal Prediction techniques and elevate your machine learning expertise.

If you're eager to manage uncertainty in industry applications using Python, 'Practical Guide to Applied Conformal Prediction in Python' is the ultimate guide for you. Order your copy today and propel your career to new heights!

What you will learn

• 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 & 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

Who This Book Is For

This book is for people interested in Conformal Prediction – data scientists, machine learning engineers, academics, researchers, software developers, students, data analysts, statisticians.

Table of Contents

1. Introducing Conformal Prediction
2. Overview of Conformal Prediction
3. Fundamentals of Conformal Prediction
4. Validity and efficiency of conformal prediction
5. Types of conformal predictors
6. Conformal Prediction for classification
7. Conformal Prediction for regression
8. Conformal Prediction for time series and forecasting
9. Conformal Prediction for Computer Vision
10. Conformal Prediction for Natural Language Processing
11. Handling imbalanced data
12. Multi-class Conformal Prediction

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