Level 2 Mathematics and Statistics Learning Workbook PDF Download

Author: Rory Barrett
Publisher:
ISBN: 9781877530593
Category : Mathematics
Languages : en
Pages : 296

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Author: Phyl Haydock
Publisher:
ISBN: 9781877459085
Category :
Languages : en
Pages :

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Book Description
For use in classroom programmes or for home study. Will cover all the skills needed to for Year 10 of the new Mathematics Curriculum. Features bite-sized sections of theory, numerous worked examples and relevant sets of exercises for student practice. Students write their answers in the workbook and all answers are given in the back of the book.

Author: Rory Barrett
Publisher:
ISBN: 9781990038556
Category :
Languages : en
Pages :

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Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446

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Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Author: Greg Port
Publisher: Hodder Education
ISBN: 9781510458437
Category : Education
Languages : en
Pages : 96

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Book Description
Reinforce learning and deepen understanding of the key concepts covered in the syllabus; an ideal course companion or homework book for use throughout the course. - Develop and strengthen skills and knowledge with a wealth of additional exercises that perfectly supplement the Student's Book - Build confidence with extra practice for each lesson to ensure that a topic is thoroughly understood before moving on - Ensure students know what to expect with hundreds of rigorous practice and exam-style questions. - Keep track of students' work with ready-to-go write-in exercises This title has not been through the Cambridge Assessment International Education endorsement process.

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.

Author: Frances Hinchliffe
Publisher:
ISBN: 9781927194041
Category : Mathematics
Languages : en
Pages : 430

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Author: Phyl Haydock
Publisher:
ISBN: 9781988586618
Category :
Languages : en
Pages :

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Book Description

Author: Phyl Haydock
Publisher:
ISBN: 9781988586649
Category :
Languages : en
Pages :

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Book Description

Author: Phyl Haydock
Publisher:
ISBN: 9780947504854
Category :
Languages : en
Pages : 346

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Book Description