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

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 fastgrowing ML framework, with Python applications. Explore cuttingedge methods to measure and manage uncertainty in industry applications. The book will explain how Conformal Prediction differs from traditional machine learning. Book DescriptionIn 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 indepth exploration of Conformal Prediction, a cuttingedge 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 handson insights and best practices for enhancing prediction reliability. The book concludes with a focus on multiclass classification nuances, providing expertlevel proficiency to seamlessly integrate Conformal Prediction into diverse industries. Practical examples in Python using realworld datasets reinforce intuitive explanations, ensuring you acquire a robust understanding of this modern framework for uncertainty quantification.This guide is a beacon for mastering Conformal Prediction in Python, providing a blend of theory and practical application. It serves as a comprehensive toolkit to enhance machine learning skills, catering to professionals from data scientists to ML engineers. What you will learn The fundamental concepts and principles of conformal prediction Learn how conformal prediction differs from traditional ML methods Apply realworld examples to your own industry applications Explore advanced topics imbalanced data and multiclass 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 forIdeal for readers with a basic understanding of machine learning concepts and Python programming, this book caters to data scientists, ML engineers, academics, and anyone keen on advancing their skills in uncertainty quantification in ML. Table of Contents Introducing Conformal Prediction Overview of Conformal Prediction Fundamentals of Conformal Prediction Validity and Efficiency of Conformal Prediction Types of Conformal Predictors Conformal Prediction for Classification Conformal Prediction for Regression Conformal Prediction for Time Series and Forecasting Conformal Prediction for Computer Vision Conformal Prediction for Natural Language Processing Handling Imbalanced Data MultiClass Conformal Prediction