A First Course in Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

"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." 
―Daniel Barbara, George Mason University, Fairfax, Virginia, USA 
"The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing ‘just in time’ the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts." 
―Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark 
"I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength…Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months." 
―David Clifton, University of Oxford, UK 
"The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book." 
―Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK 
"This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning…The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective." 
―Guangzhi Qu, Oakland University, Rochester, Michigan, USA

Business & Money

Rogers, Simon

Girolami, Mark

Economics

Chapman and Hall/CRC

The first in a visually stunning series, Information Graphics: Animal Kingdom shows just how interesting and humorous scientific information can be. Complex facts about the animal kingdom are reinterpreted as stylish information graphics that astonish, amuse, and inform, and tabbed chapters make information fast to find. Researched by the Guardian’s Datablog founder and illustrated by the award-winning designer Nicholas Blechman, this is a book of the highest pedigree.

Information Graphics: Animal Kingdom

Children's Books

Animals

Big Picture Press

The second in a visually stunning series, Information Graphics: Human Body shows just how interesting and humorous scientific information can be. Complex facts about the human body are reinterpreted as stylish infographics that astonish, amuse, and inform. Researched by the Guardian’s Datablog expert and designed by the father of infographics, Peter Grundy, this is a book of the highest pedigree.

Information Graphics: Human Body

Science, Nature & How It Works

Seeing is believing with these incredible infographics! The third in a visually stunning series of information graphics that shows just how interesting and humorous scientific information can be. Complex facts about space are reinterpreted as stylish infographics that astonish, amuse, and inform. Researched by the Guardian’s Datablog expert and illustrated by New York Times designer Jennifer Daniel, this is a book of the highest pedigree.

Information Graphics: Space

"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." ―Daniel Barbara, George Mason University, Fairfax, Virginia, USA "The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing ‘just in time’ the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts." ―Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark "I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength…Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months." ―David Clifton, University of Oxford, UK "The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book." ―Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK "This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning…The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective." ―Guangzhi Qu, Oakland University, Rochester, Michigan, USA

See the best price to sell, buy, or rent books by Rogers, Simon. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Rogers, Simon

See the best price to sell, buy, or rent books by Rogers, Simon. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

A First Course in Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Information Graphics: Animal Kingdom

Information Graphics: Human Body

Information Graphics: Space

A First Course in Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)