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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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Understanding why deep learning produces miscalibrated predictions

In the rapidly evolving field of NLP, deep learning played a pivotal role in enabling machines to process and generate language in ways that were once the exclusive domain of humans. The next section introduces the key concepts and milestones in deep learning that has significantly influenced NLP.

Introduction to deep learning in NLP

Deep learning, a subset of machine learning, relies on neural networks with many layers (hence “deep”) to analyze various data factors. In the context of NLP, deep learning has been a game-changer, enabling machines to understand and generate human language with unprecedented accuracy:

  • Evolution of architectures: The journey began with simpler architectures such as feedforward neural networks and recurrent neural networks (RNNs). With its ability to remember past information, the latter was particularly influential in sequence-based tasks such as language translation...
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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