First Course in Machine Learning / by Simon Rogers and Mark Girolami
Material type:
- 9781032937908
- D65,8(B):(S:72) Q2;Q7
Item type | Current library | Home library | Call number | Status | Barcode | |
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Central Science Library | Central Science Library | D65,8(B):(S:72) Q2;Q7 (Browse shelf(Opens below)) | Available | SL1655959 |
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D65,8(B):(C5:22) R1 Digital signal processing: An introduction | D65,8(B):(C5:22) R2 Selection of image processing techniques: From fundamentals to research front | D65,8(B):(S:72) Probabilistic Machine Learning : Advanced Topics | D65,8(B):(S:72) Q2;Q7 First Course in Machine Learning | D65,8(B):(S:72) Q5;R1 Introduction to machine learning | D65,8(B):(S:72) Q7 Machine learning : Algorithms and applications | D65,8(B):(S:72) Q8 Foundations of Machine Learning |
Includes index.
A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC." —Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden "This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade.
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