The Math(s) Fix


Book Description

Why are we all taught maths for years of our lives? Does it really empower everyone? Or fail most and disenfranchise many? Is it crucial for the AI age or an obsolete rite of passage? The Math(s) Fix: An Education Blueprint for the AI Age is a groundbreaking book that exposes why maths education is in crisis worldwide and how the only fix is a fundamentally new mainstream subject. It argues that today's maths education is not working to elevate society with modern computation, data science and AI. Instead, students are subjugated to compete with what computers do best, and lose. This is the only book to explain why being "bad at maths" may be as much the subject's fault as the learner's: how a stuck educational ecosystem has students, parents, teachers, schools, employers and policymakers running in the wrong direction to catch up with real-world requirements. But it goes further too"¬‚¬"for the first time setting out a completely alternative vision for a core computational school subject to fix the problem and seed more general reformation of education for the AI age.




The Math(s) Fix


Book Description

The Math(s) Fix: An Education Blueprint for the AI Age is a groundbreaking book that exposes why maths education is failing worldwide and how the only fix is a fundamentally new mainstream subject. It argues that today's maths education is not working to elevate society with modern computation, data science and AI. Instead, students are subjugated to compete with what computers do best, and lose.




Mathematics for Machine Learning


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.




All the Math You'll Ever Need


Book Description

A sharp mind, like a healthy body, is subject to the same ruleof nature: Use it or lose it Need a calculator just to work out a 15 percent service charge? Not exactly sure how to get the calculator to give you the figureyou need? Turn to this revised and updated edition of All the MathYou'll Ever Need, the friendliest, funniest, and easiest workoutprogram around. In no time, you'll have total command of all the powerfulmathematical tools needed to make numbers work for you. In adollars-and-cents, bottom-line world, where numbers influenceeverything, none of us can afford to let our math skills atrophy.This step-by-step personal math trainer: Refreshes practical math skills for your personal andprofessional needs, with examples based on everyday situations. Offers straightforward techniques for working with decimals and fractions. Demonstrates simple ways to figure discounts, calculatemortgage interest rates, and work out time, rate, and distance problems. Contains no complex formulas and no unnecessary technical terms.




The Math(s) Fix


Book Description

Now with a new ChatGPT-era foreword (ebook exclusive) that explains how The Math(s) Fix addresses key issues not only for the future of maths, but for AI-age education in general. This book uniquely puts the ChatGPT shock into perspective by offering the reformer's roadmap for reaction to policymakers, employers, parents, teachers, and students. Why are we all taught maths for years of our lives? Does it really empower everyone? Or fail most and disenfranchise many? Is it crucial for the AI age or an obsolete rite of passage? The Math(s) Fix: An Education Blueprint for the AI Age is a groundbreaking book that exposes why maths education is in crisis worldwide and how the only fix is a fundamentally new mainstream subject. It argues that today's maths education is not working to elevate society with modern computation, data science and AI. Instead, students are subjugated to compete with what computers do best, and lose. This is the only book to explain why being “bad at maths” may be as much the subject's fault as the learner's: how a stuck educational ecosystem has students, parents, teachers, schools, employers and policymakers running in the wrong direction to catch up with real-world requirements. But it goes further too—for the first time setting out a completely alternative vision for a core computational school subject to fix the problem and seed more general reformation of education for the AI age.




How Mathematicians Think


Book Description

To many outsiders, mathematicians appear to think like computers, grimly grinding away with a strict formal logic and moving methodically--even algorithmically--from one black-and-white deduction to another. Yet mathematicians often describe their most important breakthroughs as creative, intuitive responses to ambiguity, contradiction, and paradox. A unique examination of this less-familiar aspect of mathematics, How Mathematicians Think reveals that mathematics is a profoundly creative activity and not just a body of formalized rules and results. Nonlogical qualities, William Byers shows, play an essential role in mathematics. Ambiguities, contradictions, and paradoxes can arise when ideas developed in different contexts come into contact. Uncertainties and conflicts do not impede but rather spur the development of mathematics. Creativity often means bringing apparently incompatible perspectives together as complementary aspects of a new, more subtle theory. The secret of mathematics is not to be found only in its logical structure. The creative dimensions of mathematical work have great implications for our notions of mathematical and scientific truth, and How Mathematicians Think provides a novel approach to many fundamental questions. Is mathematics objectively true? Is it discovered or invented? And is there such a thing as a "final" scientific theory? Ultimately, How Mathematicians Think shows that the nature of mathematical thinking can teach us a great deal about the human condition itself.







The Quants


Book Description

You're a genius. Nobody plays the financial markets better than you. What could possibly go wrong? Quants - quantitative analysts - were the maths masterminds let loose on Wall Street in the belief that their brilliant, impregnable computer programs would always beat the market. But as the catastrophic events of 2007 and 2008 showed, their seemingly failproof methods were little more than ticking timebombs. Inspired by the 'Godfather of Quants' - maths-professor-turned-gambler Ed Thorp, who began applying skills learned at the Vegas tables to the financial markets back in the 1950s - the quants achieved extraordinary success and massive wealth. This book charts their rise from obscurity to boom and then to bust, explaining why they were so confident - and how they got it so disastrously wrong.




Mathematics and Computation


Book Description

An introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophy Mathematics and Computation provides a broad, conceptual overview of computational complexity theory—the mathematical study of efficient computation. With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors. Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered. Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography




The Joy of X


Book Description

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."