Download or read book Level 2 Mathematics and Statistics Externals Learning Workbook written by Phyl Haydock and published by . This book was released on 2020-11-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Level 2 Mathematics Externals Learning Workbook written by Phyl Haydock and published by . This book was released on 2015 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Level 2 Mathematics and Statistics Learning Workbook written by Rory Barrett and published by . This book was released on 2012-02 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book LWB NCEA Level 2 Achieving Maths Learning Workbook written by Phyl Haydock and published by . This book was released on 2013-07-01 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Covers the nine Level 2 Mathematics and Statistics internally assessed Standards 2.1, 2.3, 2.5, 2.8, 2.9 to 2.11, 2.13 and 2.14 and the external Standard 2.12"--Publisher information.
Download or read book Level 1 Mathematics Externals Learning Workbook written by Phyl Haydock and published by . This book was released on 2014-08-01 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Covers the four externally assessed Level 1 Mathematics and Statistics Achievement Standards 1.2 (91027), 1.3 (91028), 1.6 (91031) and 1.12 (91037). It features brief notes, clear explanations, numerous worked examples and relevant exercises with answers. Use throughout the year to support classroom work, to help with internal assessments and to revise for end-of-year exams"--Publisher's website.
Download or read book Level 2 Mathematics and Statistics AME Workbook written by Rory Barrett and published by . This book was released on 2022-05-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Level 2 Mathematics and Statistics AME Workbook written by Rory Barrett and published by . This book was released on 2018 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Covers the three external Mathematics and Statistics achievement standards ... This workbook has brief exam revision notes for end-of-year study, with examples and NCEA exam questions from 2017 and earlier years. Full answers with explanations and A, M or E grades are given"--Back cover.
Download or read book Level 2 Achieving Maths Learning Workbook written by Phyl Haydock and published by . This book was released on 2019-12-23 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Building Thinking Classrooms in Mathematics Grades K 12 written by Peter Liljedahl and published by Corwin Press. This book was released on 2020-09-28 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thinking student is an engaged student Teachers often find it difficult to implement lessons that help students go beyond rote memorization and repetitive calculations. In fact, institutional norms and habits that permeate all classrooms can actually be enabling "non-thinking" student behavior. Sparked by observing teachers struggle to implement rich mathematics tasks to engage students in deep thinking, Peter Liljedahl has translated his 15 years of research into this practical guide on how to move toward a thinking classroom. Building Thinking Classrooms in Mathematics, Grades K–12 helps teachers implement 14 optimal practices for thinking that create an ideal setting for deep mathematics learning to occur. This guide Provides the what, why, and how of each practice and answers teachers’ most frequently asked questions Includes firsthand accounts of how these practices foster thinking through teacher and student interviews and student work samples Offers a plethora of macro moves, micro moves, and rich tasks to get started Organizes the 14 practices into four toolkits that can be implemented in order and built on throughout the year When combined, these unique research-based practices create the optimal conditions for learner-centered, student-owned deep mathematical thinking and learning, and have the power to transform mathematics classrooms like never before.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Mathematics for Human Flourishing written by Francis Su and published by Yale University Press. This book was released on 2020-01-07 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The ancient Greeks argued that the best life was filled with beauty, truth, justice, play and love. The mathematician Francis Su knows just where to find them."--Kevin Hartnett, Quanta Magazine" This is perhaps the most important mathematics book of our time. Francis Su shows mathematics is an experience of the mind and, most important, of the heart."--James Tanton, Global Math Project For mathematician Francis Su, a society without mathematical affection is like a city without concerts, parks, or museums. To miss out on mathematics is to live without experiencing some of humanity's most beautiful ideas. In this profound book, written for a wide audience but especially for those disenchanted by their past experiences, an award-winning mathematician and educator weaves parables, puzzles, and personal reflections to show how mathematics meets basic human desires--such as for play, beauty, freedom, justice, and love--and cultivates virtues essential for human flourishing. These desires and virtues, and the stories told here, reveal how mathematics is intimately tied to being human. Some lessons emerge from those who have struggled, including philosopher Simone Weil, whose own mathematical contributions were overshadowed by her brother's, and Christopher Jackson, who discovered mathematics as an inmate in a federal prison. Christopher's letters to the author appear throughout the book and show how this intellectual pursuit can--and must--be open to all.
Download or read book Level 2 Systems of Equations Learning Workbook written by Vaughan Mitchell and published by . This book was released on 2015 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Download or read book Level 2 Physics Learning Workbook written by David Housden and published by . This book was released on 2012-07 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Level 1 Mathematics and Statistics AME Workbook written by Phyl Haydock and published by . This book was released on 2013-06-01 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Updated for 2013. For exam revision and practising exam questions. Covers the four Level 1 External Mathematics Achievement Standards 1.2, 1.3, 1.6 and 1.12. Features brief revision notes, examples and questions from 2012 and 2011; earlier questions formatted for use in 2013. Answers have A, M and E grades"--From publisher.
Download or read book Year 10 Mathematics and Statistics Learning Workbook written by Phyl Haydock and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
