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Author : Murray Macrae
Publisher : Longman
Page : 264 pages
File Size : 42,31 MB
Release : 2008-02-29
Category :
ISBN : 9781405833677
A new course developed by highly experienced Mathematics educators and textbook writers to cover the MoES Secondary Mathematics syllabus and to prepare students for UCE O-level Matematics examinations. The course consists of four Students' Books, each with an accompanying Teacher's Guide.
Author : Murray Macrae
Publisher : Longman
Page : 72 pages
File Size : 16,55 MB
Release : 2008-04-30
Category :
ISBN : 9781405833714
A new course developed by highly experienced Mathematics educators and textbook writers to cover the MoES Secondary Mathematics syllabus and to prepare students for UCE O-level Mathematics examinations. The course consists of four Students' Books, each with an accompanying Teacher's Guide.
Author :
Publisher :
Page : 0 pages
File Size : 34,20 MB
Release : 1981
Category :
ISBN : 9780582650589
Author : Murray F. Macrae
Publisher :
Page : 276 pages
File Size : 27,87 MB
Release : 2008-04-25
Category : Mathematics
ISBN : 9781405833592
New General Mathematics fully prepares students for the Mathematics examinations by offering full coverage of the TIE/MOEVT syllabus. The course consists of Students' Books, each with accompanying Teacher's Guides.
Author :
Publisher :
Page : 250 pages
File Size : 11,29 MB
Release : 1983
Category :
ISBN : 9780582588233
Author : Murray F. Macrae
Publisher :
Page : 156 pages
File Size : 41,58 MB
Release : 2013-08
Category :
ISBN : 9781408229781
Author :
Publisher :
Page : 0 pages
File Size : 26,50 MB
Release : 1981
Category :
ISBN : 9780582650602
Author : J.B. Channon
Publisher :
Page : 224 pages
File Size : 18,28 MB
Release : 1991-02
Category :
ISBN : 9780582588707
Author : A. O. Kalejaiye
Publisher :
Page : 59 pages
File Size : 48,35 MB
Release : 1981
Category : Mathematics
ISBN : 9780582650596
Author : Marc Peter Deisenroth
Publisher : Cambridge University Press
Page : 392 pages
File Size : 31,59 MB
Release : 2020-04-23
Category : Computers
ISBN : 1108569323
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 book's web site.