Het verboden boek 9789046707265 Ewoud Kieft€ 12,45
Chapman & Hall/CRC Machine Learning & Pattern Recognition-A
€ 21,35
Verzenden
00sinds 30 okt. '24, 08:02
Kenmerken
AuteurSimon Rogers
ConditieZo goed als nieuw
Productnummer (ISBN)9780367574642
Jaar (oorspr.)2020
Beschrijving
BoekenBalie maakt van tweedehands jouw eerste keuze. Met een Trustscore van 4,8 (excellent) en 30 dagen retour garantie maken we dat iedere dag waar.
Titel: Chapman & Hall/CRC Machine Learning & Pattern Recognition-A First Course in Machine Learning
Auteur: Simon Rogers
ISBN: 9780367574642
Conditie: Als nieuw
The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models.
"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
Titel: Chapman & Hall/CRC Machine Learning & Pattern Recognition-A First Course in Machine Learning
Auteur: Simon Rogers
ISBN: 9780367574642
Conditie: Als nieuw
The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models.
"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
Waarom je bij BoekenBalie moet zijn voor al je tweedehands boeken:
- Bestel je voor 15:00 uur? Dan vliegt het dezelfde dag nog jouw kant op!
- Meer dan 400.000 tweedehands boeken om uit te kiezen
- We checken alle boeken eigenhandig
- Vanaf 40 euro of bij 4 boeken is de verzending op onze rekening
- 30 dagen retourgarantie
Website
boekenbalie.nlZoekertjesnummer: a143947725
Populaire zoektermen
Overige Boeken Boekenrijke in Overige Boekenboeken in Overige Boekenbookseat in Overige Boekenartis historia boeken in Overige Boekensnoeck in Overige Boekende western in Overige Boekencharlie mackesy in Overige Boekenbart van loo in Overige Boekenvader zoon in Overige Boekencantecleer in Overige Boekeneeklo in Overige Boekengesigneerd in Overige Boekenharelbeke in Overige Boekenoekraine in Overige Boekenboek lara in Overige Boekenernest claes in Overige Boekenjudy hall in Boekenrijbewijs a in Boekenchristofle perles in Antiek en Kunstspinningfiets dunlop in Sport en Fitnessairco in Stacaravansmercedes garage in Mercedes-Benzdamesfiets formula in Fietsen en Brommers