Maudlin explains special relativity using a geometrical approach, emphasizing intrinsic space-time structure rather than coordinate systems or reference frames. He gives readers enough detail about special relativity to solve concrete physical problems while presenting general relativity in a more qualitative way, with an informative discussion of the geometrization of gravity, the bending of light, and black holes. Additional topics include the Twins Paradox, the physical aspects of the Lorentz-FitzGerald contraction, the constancy of the speed of light, time travel, the direction of time, and more.Introduces nonphysicists to the philosophical foundations of space-time theoryProvides a broad historical overview, from Aristotle to EinsteinExplains special relativity geometrically, emphasizing the intrinsic structure of space-timeCovers the Twins Paradox, Galilean relativity, time travel, and moreRequires only basic algebra and no formal knowledge of physicsTim Maudlin is professor of philosophy at New York University. His books include The Metaphysics within Physics and Quantum Non-Locality and Relativity.

    In "Physics Demystified" best-selling author Stan Gibilisco offers a fun, effective, and totally painless way to learn the fundamentals and general concepts of physics.With "Physics Demystified" you master the subject one simple step at a time – at your own speed. Unlike most books on physics, general principles are presented first – and the details follow. In order to make the learning process as clear and simple as possible, heavy-duty math, formulas, and equations are kept to a minimum. This unique self-teaching guide offers questions at the end of each chapter and section to pinpoint weaknesses, and a 100-question final exam to reinforce the entire book.Simple enough for a beginner but challenging enough for an advanced student, "Physics Demystified" is your direct route to learning or brushing up on physics.HERE’S EVERYTHING YOU NEED TO: * Understand the math used in physical science* Solve mass/force/acceleration problems* Create mathematical models of physical phenomena* Perform distance vs. time calculations* Determine potential and kinetic energy* Calculate the wavelength of sounds and radio signals* Understand visible light interference patterns* Calculate the energy and frequency of a moving particle* Understand atomic structure* Learn about electric current, voltage, resistance, power, and energy

    But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and HadoopDoing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    In this richly illustrated book, accessible examples are used to show how information theory can be understood in terms of everyday games like '20 Questions', and the simple MatLab programs provided give hands-on experience of information theory in action. Written in a tutorial style, with a comprehensive glossary, this text represents an ideal primer for novices who wish to become familiar with the basic principles of information theory.Download chapter 1 from http://jim-stone.staff.shef.ac.uk/Boo...

    Calculus is not a prerequisite, although examples and exercises using very basic calculus are included (labeled Calculus Required.) The most technology-friendly text on the market, Introductory Linear Algebra is also the most flexible. By omitting certain sections, instructors can cover the essentials of linear algebra (including eigenvalues and eigenvectors), to show how the computer is used, and to introduce applications of linear algebra in a one-semester course.