High-speed Math Self-taught PDF Download
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Author: Lester Meyers
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 0
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Book Description
Author: Lester Meyers
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 0
Get Book Here
Book Description
Author: Lester Meyers
Publisher: Krieger Publishing Company
ISBN: 9780882752402
Category : Mathematics
Languages : en
Pages : 532
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Book Description
Presents short-cuts and time-saving methods of doing mathematical calculations
Author: Fred H. Croom
Publisher: Courier Dover Publications
ISBN: 0486801543
Category : Mathematics
Languages : en
Pages : 340
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Book Description
Originally published: Philadelphia: Saunders College Publishing, 1989; slightly corrected.
Author: Jakow Trachtenberg
Publisher: Souvenir Press
ISBN: 0285639951
Category : Mathematics
Languages : en
Pages : 174
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Book Description
Do high-speed, complicated arithmetic in your head using the Trachtenberg Speed System. Ever find yourself struggling to check a bill or a payslip? With The Trachtenberg Speed System you can. Described as the 'shorthand of mathematics', the Trachtenberg system only requires the ability to count from one to eleven. Using a series of simplified keys it allows anyone to master calculations, giving greater speed, ease in handling numbers and increased accuracy. Jakow Trachtenberg believed that everyone is born with phenomenal abilities to calculate. He devised a set of rules that allows every child to make multiplication, division, addition, subtraction and square-root calculations with unerring accuracy and at remarkable speed. It is the perfect way to gain confidence with numbers.
Author: Lester 1902- Meyers
Publisher: Hassell Street Press
ISBN: 9781014286024
Category :
Languages : en
Pages : 324
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Book Description
This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Author: Edward Stoddard
Publisher: Courier Corporation
ISBN: 0486319881
Category : Mathematics
Languages : en
Pages : 306
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Book Description
Entertaining, easy-to-follow suggestions for developing greater speed and accuracy in doing mathematical calculations. Surefire methods for multiplying without carrying, mastering fractions, working quickly with decimals, handling percentages, and much more.
Author: Arthur Benjamin
Publisher: Crown
ISBN: 030734746X
Category : Mathematics
Languages : en
Pages : 306
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Book Description
These simple math secrets and tricks will forever change how you look at the world of numbers. Secrets of Mental Math will have you thinking like a math genius in no time. Get ready to amaze your friends—and yourself—with incredible calculations you never thought you could master, as renowned “mathemagician” Arthur Benjamin shares his techniques for lightning-quick calculations and amazing number tricks. This book will teach you to do math in your head faster than you ever thought possible, dramatically improve your memory for numbers, and—maybe for the first time—make mathematics fun. Yes, even you can learn to do seemingly complex equations in your head; all you need to learn are a few tricks. You’ll be able to quickly multiply and divide triple digits, compute with fractions, and determine squares, cubes, and roots without blinking an eye. No matter what your age or current math ability, Secrets of Mental Math will allow you to perform fantastic feats of the mind effortlessly. This is the math they never taught you in school.
Author: George Shoobridge Carr
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages :
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Book Description
Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624
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Book Description
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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Book Description
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.
