Gateway 2nd Edition - Build Up to B1
Author: DAVID. SPENCER
Publisher:
Published: 2014-12
Total Pages:
ISBN-13: 9781786325273
DOWNLOAD EBOOKNo other description available.
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Author: DAVID. SPENCER
Publisher:
Published: 2014-12
Total Pages:
ISBN-13: 9781786325273
DOWNLOAD EBOOKNo other description available.
Author: David Spencer
Publisher:
Published: 2011
Total Pages: 160
ISBN-13: 9780230723443
DOWNLOAD EBOOKGateway is an academically-rich five-level course designed to lead teenage students to success in school-leaving and university entrance exams and prepare them for university and the world of work.
Author: Gill Holley
Publisher: GATEWAY 2ND EDITION
Published: 2016-03-10
Total Pages: 96
ISBN-13: 9780230470972
DOWNLOAD EBOOKAuthor: Anna Cole
Publisher:
Published: 2011-01-01
Total Pages:
ISBN-13: 9780230417229
DOWNLOAD EBOOKHelps students prepare and practise for their school-leaving exams and equips them with lifelong learning and study skills. Taking an inductive approach to Grammar, this title revises and extends the students' knowledge of grammar and vocabulary through varied skills-based activities that recycle, revise, evaluate and develop language skills.
Author: David Spencer
Publisher: GATEWAY 2ND EDITION
Published: 2015-12-31
Total Pages: 96
ISBN-13: 9780230470910
DOWNLOAD EBOOKAuthor: Annie Cornford
Publisher: Macmillan Elt
Published: 2010-12-30
Total Pages: 128
ISBN-13: 9780230723511
DOWNLOAD EBOOKHelps students prepare and practise for their school-leaving exams and equips them with lifelong learning and study skills. Taking an inductive approach to Grammar, this title revises and extends the students' knowledge of grammar and vocabulary through varied skills-based activities that recycle, revise, evaluate and develop language skills.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
Published: 2020-04-23
Total Pages: 392
ISBN-13: 1108569323
DOWNLOAD EBOOKThe 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.
Author: Lynda Edwards
Publisher: GATEWAY 2ND EDITION
Published: 2015-12-31
Total Pages: 104
ISBN-13: 9780230470880
DOWNLOAD EBOOKAuthor: David A. Clunie
Publisher: PixelMed Publishing
Published: 2000
Total Pages: 396
ISBN-13: 0970136900
DOWNLOAD EBOOKAuthor: Gill Holley
Publisher:
Published: 2017-03-16
Total Pages: 96
ISBN-13: 9781786323170
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