Gaussian Processes for Machine Learning
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to...
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272 pages
2006-01-10 Published
Pattern Recognition and Machine Learning
This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers...
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798 pages
2007-02-01 Published
Interpretable Machine Learning
Interpretable Machine Learning is a comprehensive guide to making machine learning models interpretable "Pretty convinced this is the best book out there on the subject" – Brian Lewis, Data Scientist...
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328 pages
2024-05-26 Published
Efficient Learning Machines
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning...
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287 pages
2015-04-30 Published
Machine Learning with Neural Networks
This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the...
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241 pages
2021-10-28 Published
The Amazing Journey of Reason
Organisms, or organized, living, systems. What's their origin? Why and how did they evolve? The Amazing Journey of Reason analyses the evolution of complex structures in the universe -from the...
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129 pages
2019-12-07 Published
Deep Learning (Adaptive Computation and Machine Learning series)
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers...
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800 pages
2017-01-03 Published
An Introduction to Statistical Learning, 2nd Edition: with Applications in R
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged...
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622 pages
2022-07-30 Published
Probabilistic Machine Learning
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine...
2 like counts
944 pages
2022-02-01 Published
Deep Learning for Coders with fastai and PyTorch
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results...
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350 pages
2020-07-31 Published
Fairness and Machine Learning
An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning. Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual...
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320 pages
2023-12-28 Published
An Introduction to Deep Reinforcement Learning
Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex decision-making tasks...
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156 pages
2019-03-31 Published