Title
A First Course in Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition),Used
Delivery time: 8-12 business days (International)
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 OrtizArroyo, 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 strengthOverall, this is a pragmatic and helpful book, which is wellaligned 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 firstyear graduate students, as well as individuals who want to explore the field of machine learningThe 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
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Shipping & Returns
Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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