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| Author | : Barbara A. Oakley |
| Publisher | : TarcherPerigee |
| Total Pages | : 338 |
| Release | : 2014-07-31 |
| Genre | : Mathematics |
| ISBN | : 039916524X |
Engineering professor Barbara Oakley knows firsthand how it feels to struggle with math. In her book, she offers you the tools needed to get a better grasp of that intimidating but inescapable field.
| Author | : Barbara Oakley, PhD |
| Publisher | : Penguin |
| Total Pages | : 258 |
| Release | : 2018-08-07 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 052550446X |
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
| Author | : Alice Aspinall |
| Publisher | : FriesenPress |
| Total Pages | : 29 |
| Release | : 2018-10-16 |
| Genre | : Juvenile Fiction |
| ISBN | : 1525533746 |
How do you approach a math problem that challenges you? Do you keep trying until you reach a solution? Or are you like Amy, who gets frustrated easily and gives up? Amy is usually a happy and enthusiastic student in grade five who loves to dance, but she is struggling with a tough math assignment. She doesn’t think she is good at math because her classmates always get the answers faster than she does and sometimes she uses her fingers to help her count. Even though her mom tries to help her, Amy is convinced she just cannot do math. She decides not to do the assignment at all since she thinks she wouldn’t do well anyway. As Amy goes about her day, her experiences at ballet class, the playground, and gym class have her thinking back to how she gave up on her math assignment. She starts to notice that hard-work, practice, and dedication lead to success, thanks to her friends and teachers. She soon comes to understand that learning math is no different than learning any other skill in life. With some extra encouragement from her math teacher, a little help from her mom, and a new attitude, Amy realizes that she can do math!
| Author | : United States. Congress. House. Committee on Science |
| Publisher | : |
| Total Pages | : 280 |
| Release | : 1999 |
| Genre | : Education |
| ISBN | : |
This document presents the hearing before the Committee on Science in the House of Representatives on why and how math and science should be learned. It includes oral opening statements by various House representatives. Appendix 1 presents written opening statements from members of the subcommittee on basic research. Appendix 2 features written testimony, biographies, financial disclosures, and answers to post-hearing questions. Materials for the record are listed in the third appendix and include "Preparing Our Children: Math and Science Education in the National Interest" and "Winning the Skills Race: A Council on Competitiveness Report on Mathematics and Science Education". (ASK)
| Author | : Jordan Ellenberg |
| Publisher | : Penguin Press |
| Total Pages | : 480 |
| Release | : 2014-05-29 |
| Genre | : Mathematics |
| ISBN | : 1594205221 |
A brilliant tour of mathematical thought and a guide to becoming a better thinker, How Not to Be Wrong shows that math is not just a long list of rules to be learned and carried out by rote. Math touches everything we do; It's what makes the world make sense. Using the mathematician's methods and hard-won insights-minus the jargon-professor and popular columnist Jordan Ellenberg guides general readers through his ideas with rigor and lively irreverence, infusing everything from election results to baseball to the existence of God and the psychology of slime molds with a heightened sense of clarity and wonder. Armed with the tools of mathematics, we can see the hidden structures beneath the messy and chaotic surface of our daily lives. How Not to Be Wrong shows us how--Publisher's description.
| Author | : Steven Henry Strogatz |
| Publisher | : Houghton Mifflin Harcourt |
| Total Pages | : 333 |
| Release | : 2012 |
| Genre | : Mathematics |
| ISBN | : 0547517653 |
A delightful tour of the greatest ideas of math, showing how math intersects with philosophy, science, art, business, current events, and everyday life, by an acclaimed science communicator and regular contributor to the "New York Times."
| Author | : Diane L. Ronis |
| Publisher | : Corwin Press |
| Total Pages | : 353 |
| Release | : 2008 |
| Genre | : Education |
| ISBN | : 1412955599 |
This title provides teachers with the tools they need to help students learn in an integrated, real-world instructional environment.
| Author | : Thomas A. Garrity |
| Publisher | : 清华大学出版社有限公司 |
| Total Pages | : 380 |
| Release | : 2004 |
| Genre | : Mathematics |
| ISBN | : 9787302090854 |
| Author | : Marc Peter Deisenroth |
| Publisher | : Cambridge University Press |
| Total Pages | : 392 |
| Release | : 2020-04-23 |
| Genre | : Computers |
| ISBN | : 1108569323 |
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 | : Serge Lang |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 300 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461210704 |
This is a short text in linear algebra, intended for a one-term course. In the first chapter, Lang discusses the relation between the geometry and the algebra underlying the subject, and gives concrete examples of the notions which appear later in the book. He then starts with a discussion of linear equations, matrices and Gaussian elimination, and proceeds to discuss vector spaces, linear maps, scalar products, determinants, and eigenvalues. The book contains a large number of exercises, some of the routine computational type, while others are conceptual.
