Math to Know PDF Download

Author: Mary C. Cavanagh
Publisher: Great Source Education Group
ISBN: 9780669535976
Category : Mathematics
Languages : en
Pages : 0

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Book Description
A math resource for school and home.

Author: Thomas A. Garrity
Publisher: 清华大学出版社有限公司
ISBN: 9787302090854
Category : Mathematics
Languages : en
Pages : 380

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Book Description

Author: Anne Zeman
Publisher: Scholastic
ISBN: 9780439625227
Category : Juvenile Nonfiction
Languages : en
Pages : 152

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Book Description
Covers number systems, basic functions, measurement, geometry, money, graphs, statistics, probability, and computers.

Author: David Jackman Whitin
Publisher: Heinemann Educational Books
ISBN:
Category : Education
Languages : en
Pages : 228

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Book Description
Demonstrates the potential for literature in learnersin a variety of mathematical investigations.

Author: Michael Goldsmith
Publisher: Penguin
ISBN: 1606524755
Category : Mathematics
Languages : en
Pages : 217

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Book Description
Math, so often a mystery to children, is simply explained in I Wish I Knew That Math. With clear, commonsense explanations of mathematical concepts and fun and interesting applications, this book is a great way to increase your understanding of math. The concepts addressed include, but are certainly not limited to: Basic operations – addition, subtraction, multiplication and division The math behind money The connections between math and music Irrational numbers – Why did Pythagoras have one of his followers killed just for talking about the square root of 2? The value of zero Angles – from acute, all the way to reflexive Coordinates and the Cartesian plane Probability – What is the likelihood of being struck by lightning? Logic – induction, deduction and Sherlock Holmes Computers and algorithms Code breaking – from ancient Rome to super computers With its readable style and engaging examples, I Wish I Knew That: Math can give children a head start or a helping hand in their understanding of math. Even grownups could learn a thing or two that they may have forgotten or maybe things they never learned at all!

Author: Clifford A. Pickover
Publisher: Union Square + ORM
ISBN: 1402797494
Category : Mathematics
Languages : en
Pages : 937

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Book Description
The Neumann Prize–winning, illustrated exploration of mathematics—from its timeless mysteries to its history of mind-boggling discoveries. Beginning millions of years ago with ancient “ant odometers” and moving through time to our modern-day quest for new dimensions, The Math Book covers 250 milestones in mathematical history. Among the numerous delights readers will learn about as they dip into this inviting anthology: cicada-generated prime numbers, magic squares from centuries ago, the discovery of pi and calculus, and the butterfly effect. Each topic is lavishly illustrated with colorful art, along with formulas and concepts, fascinating facts about scientists’ lives, and real-world applications of the theorems.

Author: Casey Gonzalez
Publisher: Teaching Resources
ISBN: 9780545174565
Category : Mathematics
Languages : en
Pages : 0

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Book Description
300 reproducible activity sheets that target and reinforce the essential math skills kids need to know.

Author: Rachel Thomas
Publisher: Apple Press
ISBN: 9781845436452
Category : Mathematics
Languages : en
Pages : 0

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Book Description
Everybody knows and understands Pythagoras' theorem, but Maths Squared introduces you to the world of Einstein's relativity theory, Euclidean geometry, and the butterfly effect.

Author: Ronald T. Kneusel
Publisher: No Starch Press
ISBN: 1718501900
Category : Computers
Languages : en
Pages : 346

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Book Description
Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits. With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network. In addition you’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad/Adadelta.

Author: Brent Davis
Publisher: Routledge
ISBN: 1135097860
Category : Education
Languages : en
Pages : 141

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Book Description
What sorts of mathematics competencies must teachers have in order to teach the discipline well? This book offers a novel take on the question. Most research is focused on explicit knowledge–that is, on the sorts of insights that might be specified, catalogued, taught, and tested. In contrast, this book focuses on the tacit dimensions of teachers’ mathematics knowledge that precede and enable their competencies with formal mathematics. It highlights the complexity of this knowledge and offers strategies to uncover it, analyze it, and re-synthesize it in ways that will make it more available for teaching. Emerging from 10 years of collaborative inquiry with practicing teachers, it is simultaneously informed by the most recent research and anchored to the realities of teachers’ lives in classrooms.