A comprehensive introduction to network flows that brings together the classic and the contemporary aspects of the field, and provides an integrative view of theory, algorithms, and applications.

An examination of the methods and techniques used in the analysis and design phases of Information System development. Emphasis is placed upon the application of object technology in enterprise information systems (EIS) with UML being used throughout. Through its excellent balance of practical explanation and theoretical insight the book manages to avoid unnecessary, complicating details without sacrificing rigor. Examples of real-world scenarios are used throughout, giving the reader an understanding of what really goes on within the field of Software Engineering.

Following his blockbuster biography of Steve Jobs, The Innovatorsis Walter Isaacson's story of the people who created the computer and the Internet. It is destined to be the standard history of the digital revolution and a guide to how innovation really works. What talents allowed certain inventors and entrepreneurs to turn their disruptive ideas into realities? What led to their creative leaps? Why did some succeed and others fail? In his exciting saga, Isaacson begins with Ada Lovelace, Lord Byron's daughter, who pioneered computer programming in the 1840s. He then explores the fascinating personalities that created our current digital revolution, such as Vannevar Bush, Alan Turing, John von Neumann, J.C.R. Licklider, Doug Engelbart, Robert Noyce, Bill Gates, Steve Wozniak, Steve Jobs, Tim Berners-Lee and Larry Page. This is the story of how their minds worked and what made them so creative. It's also a narrative of how their ability to collaborate and master the art of teamwork made them even more creative. For an era that seeks to foster innovation, creativity and teamwork, this book shows how they actually happen.

The best selling 'Algorithmics' presents the most important, concepts, methods and results that are fundamental to the science of computing. It starts by introducing the basic ideas of algorithms, including their structures and methods of data manipulation. It then goes on to demonstrate how to design accurate and efficient algorithms, and discusses their inherent limitations. As the author himself says in the preface to the book; 'This book attempts to present a readable account of some of the most important and basic topics of computer science, stressing the fundamental and robust nature of the science in a form that is virtually independent of the details of specific computers, languages and formalisms'.

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. * Foundational reinforcement learning concepts and methods * The most popular deep reinforcement learning agents solving high-dimensional environments * Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

* This Revision Workbook delivers hassle-free question practice, covering one topic per page and avoiding lengthy set up time. * Build your confidence with guided practice questions, before moving onto unguided questions and practice tests. * With one-to-one page correspondence between the Workbook and the Revision Guide, this hugely popular Revision series offers the best value available for BTEC learners. * Covers both externally assessed Units for 2012 BTEC First in Information and Creative Technology (Units 1 and 2).

The financial industry is adopting Python at an increasing rate. Top hedge funds use the language on a daily basis for quantitative research, data exploration, and analysis and for prototyping, testing, and executing trading strategies. There's also a rise in trading activity by individuals and small groups of traders, including many from the technology world. This book is ideal for Python developers, tech-savvy discretionary traders, data analysts, and people who want to become Algo trading professionals or trade their own funds. Author Yves Hilpisch focuses on the practical application of programming to trading rather than theoretical computer science. If you're looking for a guide to help you perform algorithmic, fully-automated trading, this book is for you.

SYSTEMS ANALYSIS AND DESIGN, TENTH EDITION offers a practical, visually appealing approach to information systems development. The integrated Video Learning Sessions available via CourseMate will increase engagement and improve student understanding of the course material. Throughout the book, real-world case studies emphasize critical thinking and IT skills in a dynamic, business-related environment. Numerous projects, assignments, and end-of-chapter exercises, accessible only in CourseMate, provide hands-on practice. The new Tenth Edition will help prepare students for success in today's intensely competitive business world. CourseMate includes an integrated e-book, interactive activities and quizzes as well as the brand new Engagement Tracker feature. In addition, CourseMate is the only place to gain access to the SCR case study.

Business Research Methods will show your students how to undertake all parts of their research through this clear structured guide. Christina Quinlan's qualitative and holistic approaches are combined with William Zikmund's quantitative and advanced methods to give your students a broad spectrum of approaches for their research project. It is a comprehensive and interesting text that is essential reading for any business student taking a research methods module. Each stage of the research process is considered, including ethics and philosophical frameworks.

Do you want reliable code for the latest methods in scientific computing? This CD-ROM contains all the source code from the new, and all previous, editions and language versions of Numerical Recipes. Included are: Numerical Recipes, Third Edition: complete source code in C++, with many brand-new routines Numerical Recipes, Second Edition: complete source code in C, Fortran 77, and Fortran 90 Numerical Recipes, First Edition: complete source code in Pascal and BASIC plus third-party ports of the code to Modula 2 and Common Lisp The CDROM also features an archive of difficult-to-find historical materials, including Baker's C Tools and More C Tools, Lau's Numerical Library in C for Scientists and Engineers, the influential NUMAL Algol 60 library from the Mathematisch Centrum in Amsterdam, and more than 250 MB of physically generated and multiply encrypted random bytes. Compatible with all computers and operating systems, the CDROM includes a Personal Single-User License that allows an individual to use the copyrighted code on any number of computers (no more than one at a time). For support or more general license information visit at www.nr.com.

*Information Technology for Management by Turban, Volonino, and Wood engages students with up-to-date coverage of the most important IT trends today. * Over the years, this leading IT textbook had distinguished itself with an emphasis on illustrating the use of cutting edge business technologies for achieving managerial goals and objectives. * The 10th Edition continues this tradition with coverage of emerging trends in Mobile Computing and Commerce, IT virtualization, Social Media, Cloud Computing and the Management and Analysis of Big Data along with advances in more established areas of Information Technology.

Alan Turing (1912-1954) made seminal contributions to mathematical logic, computation, computer science, artificial intelligence, cryptography and theoretical biology. In this volume, outstanding scientific thinkers take a fresh look at the great range of Turing's contributions, on how the subjects have developed since his time, and how they might develop still further. The contributors include Martin Davis, J. M. E. Hyland, Andrew R. Booker, Ueli Maurer, Kanti V. Mardia, S. Barry Cooper, Stephen Wolfram, Christof Teuscher, Douglas Richard Hofstadter, Philip K. Maini, Thomas E. Woolley, Eamonn A. Gaffney, Ruth E. Baker, Richard Gordon, Stuart Kauffman, Scott Aaronson, Solomon Feferman, P. D. Welch and Roger Penrose. These specially commissioned essays will provoke and engross the reader who wishes to understand better the lasting significance of one of the twentieth century's deepest thinkers.

Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. What to expect: * Master 128 algorithms in Python. * Discover the right way to tackle a problem and quickly implement a solution of low complexity. * Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm, plus lesser known data structures like Fenwick trees and Knuth's dancing links. * A framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. * Python code in the book and on the companion website.

Algorithms play a central role both in the theory and in the practice of computing. The goal of the authors was to write a textbook that would not trivialize the subject but would still be readable by most students on their own. The book contains over 120 exercises. Some of them are drills; others make important points about the material covered in the text or introduce new algorithms not covered there. The book also provides programming projects. From the Table of Contents: Chapter 1: Basic knowledge of Mathematics, Relations, Recurrence relation and Solution techniques, Function and Growth of functions. Chapter 2: Different Sorting Techniques and their analysis. Chapter 3: Greedy approach, Dynamic Programming, Brach and Bound techniques, Backtracking and Problems, Amortized analysis, and Order Statics. Chapter 4: Graph algorithms, BFS, DFS, Spanning Tree, Flow Maximization Algorithms. Shortest Path Algorithms. Chapter 5: Binary search tree, Red black Tree, Binomial heap, B-Tree and Fibonacci Heap. Chapter 6: Approximation Algorithms, Sorting Networks, Matrix operations, Fast Fourier Transformation, Number theoretic Algorithm, Computational geometry Randomized Algorithms, String matching, NP-Hard, NP-Completeness, Cooks theorem.

Before digital computers ever existed, Alan Turing envisioned their power and versatility...but also proved what computers could never do.

In an extraordinary and ultimately tragic life that unfolded like a novel, Turing helped break the German Enigma code to turn the tide of World War II, later speculated on artificial intelligence, fell victim to the homophobic witchhunts of the early 1950s, and committed suicide at the age of 41. Yet Turing is most famous for an eerily prescient 1936 paper in which he invented an imaginary computing machine, explored its capabilities and intrinsic limitations, and established the foundations of modern-day programming and computability.

This absorbing book expands Turing's now legendary 36-page paper with extensive annotations, fascinating historical context, and page-turning glimpses into his private life. From his use of binary numbers to his exploration of concepts that today's programmers will recognize as RISC processing, subroutines, algorithms, and others, Turing foresaw the future and helped to mold it. In our post-Turing world, everything is a Turing Machine -- from the most sophisticated computers we can build, to the hardly algorithmic processes of the human mind, to the information-laden universe in which we live.

Learning to program isn't just learning the details of a programming language: to become a good programmer you have to become expert at debugging, testing, writing clear code and generally unsticking yourself when you get stuck, while to do well in a programming course you have to learn to score highly in coursework and exams. Featuring tips, stories and explanations of key terms, this book teaches these skills explicitly. Examples in Python, Java and Haskell are included, helping you to gain transferable programming skills whichever language you are learning. Intended for students in Higher or Further Education studying early programming courses, it will help you succeed in, and get the most out of, your course, and support you in developing the software engineering habits that lead to good programs.

Based on extensive customer feedback, DISCOVERING COMPUTERS (c)2014 has been completely reexamined and revised to reflect the evolving needs of the concepts portion of the Introductory Computing course. This exciting new edition maintains many longstanding hallmarks, but is now highly focused on relevancy to provide students only with what they really need to know to be successful digital citizens in college and beyond. To better reflect the importance of certain topics in today's digital world, coverage of enterprise computing, ethics, Internet research skills, mobile computing, operating systems (other than Windows), browsers, security, and Web 2.0 has been expanded and integrated. New critical thinking and problem solving exercises are included in every feature throughout the text, engaging students in regular practice of higher-order thinking skills. In addition, students have more opportunity for hands-on practice with the completely revised end-of-chapter activities. With these enhancements and more, the new DISCOVERING COMPUTERS is an even more engaging teaching and learning tool for your classroom.

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art.

Model checking is one of the most successful verification techniques and has been widely adopted in traditional computing and communication hardware and software industries. This book provides the first systematic introduction to model checking techniques applicable to quantum systems, with broad potential applications in the emerging industry of quantum computing and quantum communication as well as quantum physics. Suitable for use as a course textbook and for self-study, graduate and senior undergraduate students will appreciate the step-by-step explanations and the exercises included. Researchers and engineers in the related fields can further develop these techniques in their own work, with the final chapter outlining potential future applications.

Although it is popularly assumed that the history of computing before the second half of the 20th century was unimportant, in fact the Industrial Revolution was made possible and even sustained by a parallel revolution in computing technology. An examination and historiographical assessment of key developments helps to show how the era of modern electronic computing proceeded from a continual computing revolution that had arisen during the mechanical and the electrical ages. This unique volume introduces the history of computing during the "first" (steam) and "second" (electricity) segments of the Industrial Revolution, revealing how this history was pivotal to the emergence of electronic computing and what many historians see as signifying a shift to a post-industrial society. It delves into critical developments before the electronic era, focusing on those of the mechanical era (from the emergence of the steam engine to that of the electric power network) and the electrical era (from the emergence of the electric power network to that of electronic computing). In so doing, it provides due attention to the demarcations between-and associated classifications of-artifacts for calculation during these respective eras. In turn, it emphasizes the history of comparisons between these artifacts. Topics and Features: motivates exposition through a firm historiographical argument of important developments explores the history of the slide rule and its use in the context of electrification examines the roles of analyzers, graphs, and a whole range of computing artifacts hitherto placed under the allegedly inferior class of analog computers shows how the analog and the digital are really inseparable, with perceptions thereof depending on either a full or a restricted view of the computing process investigates socially situated comparisons of computing history, including the effects of a political economy of computing (one that takes into account cost and ownership of computing artifacts) assesses concealment of analog-machine labor through encasement ("black-boxing") Historians of computing, as well as those of technology and science (especially, energy), will find this well-argued and presented history of calculation and computation in the mechanical and electrical eras an indispensable resource. The work is a natural textbook companion for history of computing courses, and will also appeal to the broader readership of curious computer scientists and engineers, as well as those who generally just have a yearn to learn the contextual background to the current digital age. "In this fascinating, original work, Tympas indispensably intertwines the histories of analog and digital computing, showing them to be inseparable from the evolution of social and economic conditions. " Prof. David Mindell, MIT

A lively and engaging look at logic puzzles and their role in recreation, mathematics, and philosophy Logic puzzles were first introduced to the public by Lewis Carroll in the late nineteenth century and have been popular ever since. Games like Sudoku and Mastermind are fun and engrossing recreational activities, but they also share deep foundations in mathematical logic and are worthy of serious intellectual inquiry. Games for Your Mind explores the history and future of logic puzzles while enabling you to test your skill against a variety of puzzles yourself. In this informative and entertaining book, Jason Rosenhouse begins by introducing readers to logic and logic puzzles and goes on to reveal the rich history of these puzzles. He shows how Carroll's puzzles presented Aristotelian logic as a game for children, yet also informed his scholarly work on logic. He reveals how another pioneer of logic puzzles, Raymond Smullyan, drew on classic puzzles about liars and truthtellers to illustrate Kurt Goedel's theorems and illuminate profound questions in mathematical logic. Rosenhouse then presents a new vision for the future of logic puzzles based on nonclassical logic, which is used today in computer science and automated reasoning to manipulate large and sometimes contradictory sets of data. Featuring a wealth of sample puzzles ranging from simple to extremely challenging, this lively and engaging book brings together many of the most ingenious puzzles ever devised, including the "Hardest Logic Puzzle Ever," metapuzzles, paradoxes, and the logic puzzles in detective stories.

'Rana el Kaliouby's vision for how technology should work in parallel with empathy is bold, inspired and hopeful' Arianna Huffington, founder and CEO of Thrive Global 'This lucid and captivating book by a renowned pioneer of emotion-AI tackles one of the most pressing issues of our time: How can we ensure a future where this technology empowers rather than surveils and manipulates us?' Max Tegmark, professor of physics at Massachusetts Institute of Technology and author of Life 3.0 We are entering an empathy crisis. Most of our communication is conveyed through non-verbal cues - facial expressions, tone of voice, body language - nuances that are completely lost when we interact through our smartphones and other technology. The result is a digital universe that's emotion-blind - a society lacking in empathy. Rana el Kaliouby discovered this when she left Cairo, a newly-married, Muslim woman, to take up her place at Cambridge University to study computer science. Many thousands of miles from home, she began to develop systems to help her better connect with her family. She started to pioneer the new field of Emotional Intelligence (EI). She now runs her company, Affectiva (the industry-leader in this emerging field) that builds EI into our technology and develops systems that understand humans the way we understand one another. In a captivating memoir, Girl Decoded chronicles el Kaliouby's mission to humanise technology and what she learns about humanity along the way.