Speakable and Unspeakable in Quantum Mechanics


John Stewart Bell - 1987
    This work has played a major role in the development of our current understanding of the profound nature of quantum concepts and of the fundamental limitations they impose on the applicability of the classical ideas of space, time and locality. This book contains all of John Bell's published and unpublished papers on the conceptual and philosophical problems of quantum mechanics.

Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems


Peter Dayan - 2001
    This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site.

A Practical Guide to Quantitative Finance Interviews


Xinfeng Zhou - 2008
    In this book we analyze solutions to more than 200 real interview problems and provide valuable insights into how to ace quantitative interviews. The book covers a variety of topics that you are likely to encounter in quantitative interviews: brain teasers, calculus, linear algebra, probability, stochastic processes and stochastic calculus, finance and programming.

A First Course in Probability


Sheldon M. Ross - 1976
    A software diskette provides an easy-to-use tool for students to derive probabilities for binomial.

Getting Started with MATLAB 7: A Quick Introduction for Scientists and Engineers


Rudra Pratap - 2005
    Its broad appeal lies in its interactive environment with hundreds of built-in functions for technical computation, graphics, and animation. In addition, it provides easy extensibility with its own high-level programming language. Enhanced by fun and appealing illustrations, Getting Started with MATLAB 7: A Quick Introduction for Scientists and Engineers employs a casual, accessible writing style that shows users how to enjoy using MATLAB.

Neural Networks and Deep Learning


Michael Nielsen - 2013
    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

John Von Neumann


Norman Macrae - 1992
    This book discusses Von Neumann's work in areas such as game theory, mathematics, physics, and meteorology which formed the building blocks for the most important discoveries of the century: the modern computer, game theory, and the atom bomb.

The Complete Idiot's Guide to Game Theory


Edward C. Rosenthal - 2005
    It is based on the idea that everyone acts competitively and in his own best interest. With the help of mathematical models, it is possible to anticipate the actions of others in nearly all life's enterprises. This book includes down-to-earth examples and solutions, as well as charts and illustrations designed to help teach the concept. In The Complete Idiot's GuideĀ® to Game Theory, Dr. Edward C. Rosenthal makes it easy to understand game theory with insights into:? The history of the disciple made popular by John Nash, the mathematician dramatized in the film A Beautiful Mind? The role of social behavior and psychology in this amazing discipline? How important game theory has become in our society and why

Operations Research: Applications and Algorithms (with CD-ROM and InfoTrac)


Wayne L. Winston - 1987
    It moves beyond a mere study of algorithms without sacrificing the rigor that faculty desire. As in every edition, Winston reinforces the book's successful features and coverage with the most recent developments in the field. The Student Suite CD-ROM, which now accompanies every new copy of the text, contains the latest versions of commercial software for optimization, simulation, and decision analysis.

Algorithm Design


Jon Kleinberg - 2005
    The book teaches a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.

Multivariate Data Analysis


Joseph F. Hair Jr. - 1979
    This book provides an applications-oriented introduction to multivariate data analysis for the non-statistician, by focusing on the fundamental concepts that affect the use of specific techniques.

Introduction to Computer Theory


Daniel I.A. Cohen - 1986
    Covers all the topics needed by computer scientists with a sometimes humorous approach that reviewers found refreshing. The goal of the book is to provide a firm understanding of the principles and the big picture of where computer theory fits into the field.

Introduction to Modern Cryptography: Principles and Protocols


Jonathan Katz - 2007
    Introduction to Modern Cryptography provides a rigorous yet accessible treatment of modern cryptography, with a focus on formal definitions, precise assumptions, and rigorous proofs.The authors introduce the core principles of modern cryptography, including the modern, computational approach to security that overcomes the limitations of perfect secrecy. An extensive treatment of private-key encryption and message authentication follows. The authors also illustrate design principles for block ciphers, such as the Data Encryption Standard (DES) and the Advanced Encryption Standard (AES), and present provably secure constructions of block ciphers from lower-level primitives. The second half of the book focuses on public-key cryptography, beginning with a self-contained introduction to the number theory needed to understand the RSA, Diffie-Hellman, El Gamal, and other cryptosystems. After exploring public-key encryption and digital signatures, the book concludes with a discussion of the random oracle model and its applications.Serving as a textbook, a reference, or for self-study, Introduction to Modern Cryptography presents the necessary tools to fully understand this fascinating subject.

The Little Go Book


Karl Seguin - 2014
    It's aimed at developers who might not be quite comfortable with the idea of pointers and static typing.http://openmymind.net/The-Little-Go-B...

Matrix Computations


Gene H. Golub - 1983
    It includes rewritten and clarified proofs and derivations, as well as new topics such as Arnoldi iteration, and domain decomposition methods.