Revise for Decision Mathematics 1 PDF Download
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Author: John Hebborn
Publisher: Heinemann
ISBN: 9780435511197
Category : Juvenile Nonfiction
Languages : en
Pages : 76
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Book Description
Revision book written specifically for the Edexcel AS and A Level exams offering: worked examination questions and examples with hints on answering examination questions successfully; test-yourself section; key points reinforcing what students have learned; and answers to all questions.
Author: John Hebborn
Publisher: Heinemann
ISBN: 9780435511197
Category : Juvenile Nonfiction
Languages : en
Pages : 76
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Book Description
Revision book written specifically for the Edexcel AS and A Level exams offering: worked examination questions and examples with hints on answering examination questions successfully; test-yourself section; key points reinforcing what students have learned; and answers to all questions.
Author: Richard Parsons
Publisher: Coordination Group Publication
ISBN: 9781847628060
Category : A-level examinations
Languages : en
Pages : 204
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Book Description
AS/A Level Maths for Edexcel - Decision Maths 1: Student Book
Author:
Publisher:
ISBN:
Category : Decision making
Languages : en
Pages : 464
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Book Description
Author: Michael Kenwood
Publisher: Heinemann
ISBN: 9780435511104
Category : Juvenile Nonfiction
Languages : en
Pages : 68
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Book Description
Revision book written specifically for the Edexcel AS and A Level exams offering: worked examination questions and examples with hints on answering examination questions successfully; test-yourself section; key points reinforcing what students have learned; and answers to all questions.
Author: Richard Parsons
Publisher: Coordination Group Publication
ISBN: 9781847627971
Category : A-level examinations
Languages : en
Pages : 194
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Book Description
AS/A Level Maths for AQA - Decision Maths 1: Student Book
Author: John Hebborn
Publisher: Heinemann
ISBN: 9780435511319
Category : Decision making
Languages : en
Pages : 76
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Book Description
This book covers the key topics that are tested in the Decision maths 2 exam paper.
Author: Pledger
Publisher: Heinemann
ISBN: 9780435511227
Category : Mathematics
Languages : en
Pages : 88
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Book Description
The clear route to A Level success - new Core titles for the new specification Written by the same authors as the textbooks for a complete match, so are ideal for use alongside the course books. Worked examination questions and examples with hints on answering questions successfully help students push for those top grades. A test-yourself section makes sure students are fully prepared for the exam. Key points help reinforce learning and help students reach their best potential. Answers to all the questions ensure students can check their work. Written by experienced Senior Examiners.
Author: Geoff Mannall
Publisher: Heinemann
ISBN: 9780435510886
Category : Mathematics
Languages : en
Pages : 292
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Book Description
A syllabus-specific textbook providing worked examples, exam-level questions and many practice exercises, in accordance to the new Edexcel AS and Advanced GCE specification.
Author: Greg Attwood
Publisher: Heinemann
ISBN: 9780435510855
Category : Mathematics
Languages : en
Pages : 148
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Book Description
A syllabus-specific textbook providing worked examples, exam-level questions and many practice exercises, in accordance to the new Edexcel AS and Advanced GCE specification.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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Book 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 book's web site.
