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This revision guide is clearly written by experienced examiners and teachers and is packed full of information, quick-check revision questions, hints and tips from examiners, and practice exam-style questions, to provide students with that extra help they need for exam preparation.
Exam Board: OCR Level: A-level Subject: Biology First Teaching: September 2015 First Exam: June 2016 This is an OCR endorsed resource Encourage students to learn independently and build on their knowledge with this textbook that leads students seamlessly from basic biological concepts to more complicated theories. - Develop experimental, analytical and evaluation skills with activities that introduce the practicals required by OCR and other experimental investigations in Biology - Provide assessment guidance with synoptic questions and multiple choice questions throughout the book, and revision tips and skills all in one chapter - Strengthen understanding of key concepts with contemporary and engaging examples, illustrated with accessible diagrams and images - Give students the opportunity to apply their knowledge and understanding of all aspects of practical work with Test Yourself Questions and Exam Practice Questions - Offer detailed guidance and examples of method with a dedicated 'Maths in Biology' chapter and mathematical support throughout - Develop understanding with free online access to answers, an extended glossary, learning outcomes and topic summaries OCR A Level Biology Student Book 1 includes AS Level
New 2017 Cambridge A Level Maths and Further Maths resources help students with learning and revision. Written for the OCR AS/A Level Mathematics specifications for first teaching from 2017, this print Student Book covers the content for AS and the first year of A Level. It balances accessible exposition with a wealth of worked examples, exercises and opportunities to test and consolidate learning, providing a clear and structured pathway for progressing through the course. It is underpinned by a strong pedagogical approach, with an emphasis on skills development and the synoptic nature of the course. Includes answers to aid independent study.
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Please note this title is suitable for any student studying: Exam Board: AQA Level: A Level Subject: Biology First teaching: September 2015 First exams: June 2017 Fully revised and updated for the new linear qualification, written and checked by curriculum and specification experts, this Student Book supports and extends students through the new course whilst delivering the maths, practical and synoptic skills needed to succeed in the new A Levels and beyond. The book uses clear straightforward explanations to develop true subject knowledge and allow students to link ideas together while developing essential exam skills.
This title covers the entire syllabus for Cambridge International Examinations' International AS and A Level Biology (9700). It is divided into separate sections for AS and A Level making it ideal for students studying both the AS and the A Level and also those taking the AS examinations at the end of their first year. - Explains difficult concepts using language that is appropriate for students around the world - Provides practice throughout the course with carefully selected past paper questions at the end of each chapter We are working with Cambridge International Examinations to gain endorsement for this title.
Written by experienced authors and practising teachers the Essentials student book matches the OCR specifications for AS Biology and Human Biology.
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
This volume provides a summary of the findings that educational research has to offer on good practice in school science teaching. It offers an overview of scholarship and research in the field, and introduces the ideas and evidence that guide it.