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Author : David Halliday
Publisher :
Page : pages
File Size : 31,90 MB
Release : 2010-09-17
Category :
ISBN : 9780470911273
Author : David Halliday
Publisher :
Page : pages
File Size : 35,92 MB
Release : 2009-07-10
Category :
ISBN : 9780470575154
Author : John D. Cutnell
Publisher :
Page : pages
File Size : 26,48 MB
Release : 2009-08-22
Category :
ISBN : 9780470575215
Author : David Halliday
Publisher : Wiley
Page : pages
File Size : 37,64 MB
Release : 2019-08-20
Category : Science
ISBN : 9781119669593
Author : David Halliday
Publisher : John Wiley & Sons
Page : pages
File Size : 48,65 MB
Release : 2007-03-27
Category :
ISBN : 9780470136867
Author : David Halliday
Publisher : John Wiley & Sons
Page : 72 pages
File Size : 11,82 MB
Release : 2010-03-15
Category : Science
ISBN : 0470469110
This book arms engineers with the tools to apply key physics concepts in the field. A number of the key figures in the new edition are revised to provide a more inviting and informative treatment. The figures are broken into component parts with supporting commentary so that they can more readily see the key ideas. Material from The Flying Circus is incorporated into the chapter opener puzzlers, sample problems, examples and end-of-chapter problems to make the subject more engaging. Checkpoints enable them to check their understanding of a question with some reasoning based on the narrative or sample problem they just read. Sample Problems also demonstrate how engineers can solve problems with reasoned solutions. INCLUDES PARTS 1-4 PART 5 IN FUNDAMENTALS OF PHYSICS, EXTENDED
Author : Avrim Blum
Publisher : Cambridge University Press
Page : 433 pages
File Size : 47,27 MB
Release : 2020-01-23
Category : Computers
ISBN : 1108617360
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author : David Halliday
Publisher :
Page : pages
File Size : 47,87 MB
Release : 2010-08-25
Category :
ISBN : 9781118004111
Author : Robert W. Stanley
Publisher : Brooks/Cole
Page : 416 pages
File Size : 18,4 MB
Release : 1987
Category : Education
ISBN : 9780156016629
Author : Halliday
Publisher :
Page : 500 pages
File Size : 47,90 MB
Release : 2013-11-15
Category :
ISBN : 9781118891469