Practical Conformal Prediction with Python PDF
Don't Just Predict. Quantify Confidence.Book DescriptionThe Most Important Prediction Is Not What the Model Says—It Is How Much You Can Trust It.Most machine learning models tell you what they predict, but few tell you how much to trust that prediction. Practical Conformal Prediction with Python changes that — presenting Conformal Prediction(CP) as a robust, distribution-free, model-agnostic frame...

Ravindra Sharma - Practical Conformal Prediction with Python

Practical Conformal Prediction with Python

Build Reliable and Trustworthy AI with Uncertainty Quantification, Prediction Intervals, Model Calibration, and Conformal Prediction in Python (English Edition)

Ravindra Sharma

Google Play

Published by
StreetLib eBooks

Language
English
Format
epub
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Description

Don't Just Predict. Quantify Confidence.Book DescriptionThe Most Important Prediction Is Not What the Model Says—It Is How Much You Can Trust It.Most machine learning models tell you what they predict, but few tell you how much to trust that prediction. Practical Conformal Prediction with Python changes that — presenting Conformal Prediction(CP) as a robust, distribution-free, model-agnostic framework for generating statistically valid confidence intervals across diverse predictive tasks in Python.You begin with the problem of model miscalibration and the mathematical foundations of Conformal Prediction, then advance through practical CP techniques for classification, regression, and forecasting using scikit-learn and statsmodels. Each chapter blends theory with implementation through structured experiments, reproducible examples, and chapter-end quizzes.The final section covers scalable and adaptive CP methods designed for large datasets and real-time applications, alongside real-world business applications across diverse domains. By the end of the book, you will have both the theoretical grounding and practical expertise to build reliable, interpretable, and trustworthy AI systems using Conformal Prediction and Python.What you will learn● Apply Conformal Prediction techniques to measure and manage uncertainty in ML models.● Implement CP methods for classification, regression, and time-series forecasting tasks.● Evaluate model validity, coverage, and efficiency through structured reproducible experiments.● Build scalable and adaptive CP methods for large datasets and real-time applications.● Use Python libraries including scikit-learn and statsmodels for CP implementation.● Apply Conformal Prediction to real-world business problems across diverse domains.Table of Contents1. The Illusion of Certainty2. The Foundations of Conformal Prediction3. Conformal Prediction for Classification4. Conformal Prediction for Regression5. Conformal Prediction for Forecasting6. Scalable Conformal Prediction7. Real-World Applications of Conformal Prediction       Index

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