{"product_id":"a-first-course-in-machine-learning-simon-rogers-9780367574642","title":"A First Course in Machine Learning","description":"\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe 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.\u003c\/p\u003e\n\u003ch3\u003eOmschrijving\u003c\/h3\u003e\n\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\"\u003cstrong\u003eA First Course in Machine Learning \u003c\/strong\u003eby 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.\"\u003cbr\u003e\u003cem\u003e-Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\"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.\"\u003cbr\u003e\u003cem\u003e-Daniel Barbara, George Mason University, Fairfax, Virginia, USA\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\"The new edition of \u003cstrong\u003eA First Course in Machine Learning \u003c\/strong\u003eby 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.\"\u003cbr\u003e\u003cem\u003e-Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\"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.\"\u003cbr\u003e\u003cem\u003e-David Clifton, University of Oxford, UK\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\"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.\" \u003cbr\u003e\u003cem\u003e-Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\"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 mach…\u003c\/p\u003e\n\u003ch3\u003eProductspecificaties\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAuteur:\u003c\/strong\u003e Simon Rogers\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSerie:\u003c\/strong\u003e Chapman \u0026amp; Hall\/CRC Machine Learning \u0026amp; Pattern Recognition\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eUitgever:\u003c\/strong\u003e Taylor \u0026amp; Francis Ltd\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eImprint:\u003c\/strong\u003e Chapman \u0026amp; Hall\/CRC\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eVerschijningsdatum:\u003c\/strong\u003e 2020-06-30\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAantal pagina's:\u003c\/strong\u003e 428\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eISBN:\u003c\/strong\u003e 9780367574642\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eThema:\u003c\/strong\u003e Econometrics and economic statistics\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBISAC:\u003c\/strong\u003e BUSINESS \u0026amp; ECONOMICS \/ Econometrics\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eOver de auteur\u003c\/h3\u003e\n\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eSimon Rogers\u003c\/strong\u003e is a lecturer in the School of Computing Science at the University of Glasgow, where he teaches a masters-level machine learning course on which this book is based. Dr. Rogers is an active researcher in machine learning, particularly applied to problems in computational biology. His research interests include the analysis of metabolomic data and the application of probabilistic machine learning techniques in the field of human-computer interaction.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eMark Girolami \u003c\/strong\u003eholds an honorary professorship in Computer Science at the University of Warwick, is an EPSRC Established Career Fellow (2012 - 2017) and previously an EPSRC Advanced Research Fellow (2007 - 2012). He is also honorary Professor of Statistics at University College London, is the Director of the EPSRC funded Research Network on Computational Statistics and Machine Learning an…\u003c\/p\u003e","brand":"Intertaal","offers":[{"title":"Default Title","offer_id":56354501886292,"sku":"9780367574642","price":53.95,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0967\/0538\/0692\/files\/9780367574642.jpg?v=1783583880","url":"https:\/\/intertaalid.nl\/en\/products\/a-first-course-in-machine-learning-simon-rogers-9780367574642","provider":"Intertaal","version":"1.0","type":"link"}