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You're reading from  Practical Guide to Applied Conformal Prediction in Python

Product typeBook
Published inDec 2023
PublisherPackt
ISBN-139781805122760
Edition1st Edition
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Author (1)
Valery Manokhin
Valery Manokhin
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Valery Manokhin

Valeriy Manokhin is the leading expert in the field of machine learning and Conformal Prediction. He holds a Ph.D.in Machine Learning from Royal Holloway, University of London. His doctoral work was supervised by the creator of Conformal Prediction, Vladimir Vovk, and focused on developing new methods for quantifying uncertainty in machine learning models. Valeriy has published extensively in leading machine learning journals, and his Ph.D. dissertation 'Machine Learning for Probabilistic Prediction' is read by thousands of people across the world. He is also the creator of "Awesome Conformal Prediction," the most popular resource and GitHub repository for all things Conformal Prediction.
Read more about Valery Manokhin

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Conformal prediction for computer vision

In this section, we will dive deeper into the diverse applications of conformal prediction in computer vision. With its broad range of problems, from image classification to object detection, computer vision presents challenges that require precise and reliable machine learning models. As we navigate these applications, we will demonstrate how conformal prediction is a robust tool to quantify the uncertainty associated with these models.

By exploring these practical examples, we aim to underscore the importance of understanding the model’s confidence in its predictions. Understanding is crucial, especially when decisions based on these predictions could have significant consequences. Conformal prediction, with its ability to provide a measure of uncertainty, can greatly aid researchers and practitioners in making informed decisions based on the outputs of their models. This improves the system’s reliability and paves the way...

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Practical Guide to Applied Conformal Prediction in Python
Published in: Dec 2023Publisher: PacktISBN-13: 9781805122760

Author (1)

author image
Valery Manokhin

Valeriy Manokhin is the leading expert in the field of machine learning and Conformal Prediction. He holds a Ph.D.in Machine Learning from Royal Holloway, University of London. His doctoral work was supervised by the creator of Conformal Prediction, Vladimir Vovk, and focused on developing new methods for quantifying uncertainty in machine learning models. Valeriy has published extensively in leading machine learning journals, and his Ph.D. dissertation 'Machine Learning for Probabilistic Prediction' is read by thousands of people across the world. He is also the creator of "Awesome Conformal Prediction," the most popular resource and GitHub repository for all things Conformal Prediction.
Read more about Valery Manokhin