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Mathematics for Machine Learning 1st Edition by Marc Peter Deisenroth (English)

Description: Mathematics for Machine Learning by Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Estimated delivery 3-12 business days Format Paperback Condition Brand New Description This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. Publisher Description The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the books web site. Author Biography Marc Peter Deisenroth is DeepMind Chair in Artificial Intelligence at the Department of Computer Science, University College London. Prior to this, he was a faculty member in the Department of Computing, Imperial College London. His research areas include data-efficient learning, probabilistic modeling, and autonomous decision making. Deisenroth was Program Chair of the European Workshop on Reinforcement Learning (EWRL) 2012 and Workshops Chair of Robotics Science and Systems (RSS) 2013. His research received Best Paper Awards at the International Conference on Robotics and Automation (ICRA) 2014 and the International Conference on Control, Automation and Systems (ICCAS) 2016. In 2018, he was awarded the Presidents Award for Outstanding Early Career Researcher at Imperial College London. He is a recipient of a Google Faculty Research Award and a Microsoft P.hD. grant. A. Aldo Faisal leads the Brain and Behaviour Lab at Imperial College London, where he is faculty at the Departments of Bioengineering and Computing and a Fellow of the Data Science Institute. He is the director of the 20Mio£ UKRI Center for Doctoral Training in AI for Healthcare. Faisal studied Computer Science and Physics at the Universität Bielefeld (Germany). He obtained a Ph.D. in Computational Neuroscience at the University of Cambridge and became Junior Research Fellow in the Computational and Biological Learning Lab. His research is at the interface of neuroscience and machine learning to understand and reverse engineer brains and behavior. Cheng Soon Ong is Principal Research Scientist at the Machine Learning Research Group, Data61, Commonwealth Scientific and Industrial Research Organisation, Canberra (CSIRO). He is also Adjunct Associate Professor at Australian National University. His research focuses on enabling scientific discovery by extending statistical machine learning methods. Ong received his Ph.D. in Computer Science at Australian National University in 2005. He was a postdoc at Max Planck Institute of Biological Cybernetics and Friedrich Miescher Laboratory. From 2008 to 2011, he was a lecturer in the Department of Computer Science at Eidgenössische Technische Hochschule (ETH) ZÜrich, and in 2012 and 2013 he worked in the Diagnostic Genomics Team at NICTA in Melbourne. Details ISBN 110845514X ISBN-13 9781108455145 Title Mathematics for Machine Learning Author Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Format Paperback Year 2020 Pages 398 Edition 1st Publisher Cambridge University Press GE_Item_ID:127213434; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. 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Price: 61.98 USD

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Mathematics for Machine Learning 1st Edition by Marc Peter Deisenroth (English)

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Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money Back

ISBN-13: 9781108455145

Book Title: Mathematics for Machine Learning

Number of Pages: 398 Pages

Publication Name: Mathematics for Machine Learning

Language: English

Publisher: Cambridge University Press

Subject: General, Computer Vision & Pattern Recognition

Item Height: 0.7 in

Publication Year: 2020

Type: Textbook

Item Weight: 28.2 Oz

Author: Cheng Soon Ong, A. Aldo Faisal, Marc Peter Deisenroth

Subject Area: Computers, Science

Item Length: 9.9 in

Item Width: 7 in

Format: Trade Paperback

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