A large number of fully worked examples demonstrate mathematical processes and encourage independent learning. Exercises are carefully graded to suit the range of students undertaking each mathematics course. Online self-marking objective response quizzes provide further opportunities to practice the multiple choice style questions included in HSC Maths exams.
Features: • The current and new versions will have the same pagination. • A large number of fully worked examples demonstrate mathematical processes and encourage independent learning. Exercises are carefully graded to suit the range of students undertaking each mathematics course • Online self-marking objective response quizzes provide further opportunities to practice the multiple choice style questions included in HSC Maths exams. 2 Unit / 3 Unit Mathematics: • Foundation questions consolidate fluency and understanding, development questions encourage students to apply their understanding to a particular context. • Extension or Challenge questions inspire further thought and development for advanced students. • The wealth of questions in these three categories enables teachers to make a selection to be attempted by students of differing abilities and provides students with opportunities to practice questions of the standard they will encounter in their HSC exams.
This series is endorsed by Cambridge International Examinations and is part of Cambridge Maths. Learners will reinforce their mathematical understanding in an enjoyable way with the fun games in this stage 3 games book resource for teachers. Instructions for teachers or parents are provided and direct links to both the course objectives and activities in the teacher's guide are made, making this the perfect resource for additional class activity or homework. All photocopiable resources needed to play the games are included in the book and on the CD, so learners can start playing straight away. Projectable instructions for the learners are also included on the CD.
This series is endorsed by Cambridge International Examinations and is part of Cambridge Maths. This teacher's resource for stage 1 will fully support teachers to get the best from their learners and effectively use the learner's book and games book. Detailed lesson plans based on the course objectives are offered, along with additional activity ideas. Teachers will be guided to formatively assess their learners' understanding. They will have the confidence to engage the class in mathematical discussion and encourage learners to justify answers and make connections between ideas. Answers to the learner's book and all photocopiable sheets required are provided. All book content, plus more, is included on the CD for convenience.
Build solid mathematical understanding and develop key conceptual connections. The inquiry-based approach integrates the MYP key concepts, helping you shift to a concept-based classroom and cement mathematical comprehension. Fully comprehensive and matched to the Revised MYP to support achievement. Progress your learners into IB Diploma - fully comprehensive and matched to the MYP Next Chapter curriculum Develop conceptual understanding in the best way for your learners - learn by mathematical unit or by key concept Drive active, critical exploration of mathematical principles - build rounded comprehension framed within the key and related concepts Develop meaningful cross-curricular connections that help learners recognize and manipulate mathematical ideas in other disciplines Support higher level thinking skills through an approach grounded in factual, conceptual and debatable questions Build a solid foundation of practical skills with extensive practice equipping learners to apply skills Fully prepare learners for the MYP eAssessment Multiplatform access, compatible with a wide range of devices Your first login will be facilitated by a printed access card that will be sent to you in the mail Includes one print course book and one online course book
An authorised reissue of the long out of print classic textbook, Advanced Calculus by the late Dr Lynn Loomis and Dr Shlomo Sternberg both of Harvard University has been a revered but hard to find textbook for the advanced calculus course for decades.This book is based on an honors course in advanced calculus that the authors gave in the 1960's. The foundational material, presented in the unstarred sections of Chapters 1 through 11, was normally covered, but different applications of this basic material were stressed from year to year, and the book therefore contains more material than was covered in any one year. It can accordingly be used (with omissions) as a text for a year's course in advanced calculus, or as a text for a three-semester introduction to analysis.The prerequisites are a good grounding in the calculus of one variable from a mathematically rigorous point of view, together with some acquaintance with linear algebra. The reader should be familiar with limit and continuity type arguments and have a certain amount of mathematical sophistication. As possible introductory texts, we mention Differential and Integral Calculus by R Courant, Calculus by T Apostol, Calculus by M Spivak, and Pure Mathematics by G Hardy. The reader should also have some experience with partial derivatives.In overall plan the book divides roughly into a first half which develops the calculus (principally the differential calculus) in the setting of normed vector spaces, and a second half which deals with the calculus of differentiable manifolds.
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.
