An Introduction to Functional Programming Through Lambda Calculus


Greg Michaelson - 1989
    This well-respected text offers an accessible introduction to functional programming concepts and techniques for students of mathematics and computer science. The treatment is as nontechnical as possible, and it assumes no prior knowledge of mathematics or functional programming. Cogent examples illuminate the central ideas, and numerous exercises appear throughout the text, offering reinforcement of key concepts. All problems feature complete solutions.

Real World Java EE Patterns--Rethinking Best Practices


Adam Bien - 2009
    :-)

Compilers: Principles, Techniques, and Tools


Alfred V. Aho - 1986
    The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation.

Functional Programming in Scala


RĂșnar Bjarnason - 2013
    As a result, functional code is easier to test and reuse, simpler to parallelize, and less prone to bugs. Scala is an emerging JVM language that offers strong support for FP. Its familiar syntax and transparent interoperability with existing Java libraries make Scala a great place to start learning FP.Functional Programming in Scala is a serious tutorial for programmers looking to learn FP and apply it to the everyday business of coding. The book guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. In it, they'll find concrete examples and exercises that open up the world of functional programming.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Computational Geometry: Algorithms and Applications


Mark de Berg - 1997
    The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In the second edition, besides revisions to the first edition, a number of new exercises have been added.

Programming Collective Intelligence: Building Smart Web 2.0 Applications


Toby Segaran - 2002
    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

Artificial Intelligence: A Modern Approach


Stuart Russell - 1994
    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

Algorithms in a Nutshell


George T. Heineman - 2008
    Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will:Solve a particular coding problem or improve on the performance of an existing solutionQuickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to useGet algorithmic solutions in C, C++, Java, and Ruby with implementation tipsLearn the expected performance of an algorithm, and the conditions it needs to perform at its bestDiscover the impact that similar design decisions have on different algorithmsLearn advanced data structures to improve the efficiency of algorithmsWith Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.

Algorithms


Sanjoy Dasgupta - 2006
    Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University

Working with UNIX Processes


Jesse Storimer - 2011
    Want to impress your coworkers and write the fastest, most efficient, stable code you ever have? Don't reinvent the wheel. Reuse decades of research into battle-tested, highly optimized, and proven techniques available on any Unix system.This book will teach you what you need to know so that you can write your own servers, debug your entire stack when things go awry, and understand how things are working under the hood.http://www.jstorimer.com/products/wor...

Mastering Excel Macros: Introduction (Book 1)


Mark Moore - 2014
    Everybody wants to learn them. You're not a programmer though. How is a non technical user going to learn how to program? You do want to use macros to make your work easier but are you really going to sit down with a huge programming textbook and work your way through every. single. boring. page? Like most people, you'll start with great enthusiasm and vigor but after a few chapters, the novelty wears off. It gets boring. I'm going to try and change that and make learning macro programming entertaining and accessible to non-techies. First of all, programming Excel macros is a huge topic. Let's eat the elephant one bite at a time. Instead of sitting down with a dry, heavy text, you will read very focused, to the point topics. You can then immediately use what you learned in the real world. This is the first lesson in the series. You will learn what macros are, how to access them, a tiny bit of programming theory (just so you have a clue as to what's going on) and how to record macros. As with all my other lessons, this one has a follow along workbook that you can use to work through the exercises. The images in the lessons are based on Excel 2013 for Windows.

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.

How to Count (Programming for Mere Mortals, #1)


Steven Frank - 2011
    unsigned numbers- Floating point and fixed point arithmeticThis short, easily understood book will quickly get you thinking like a programmer.

Programming Languages: Design and Implementation


Terrence W. Pratt - 1995
    The emphasis throughout is on fundamental concepts--readers learn important ideas, not minor language differences--but several languages are highlighted in sufficient detail to enable readers to write programs that demonstrate the relationship between a source program and its execution behavior--e.g., C, C++, JAVA, ML, LISP, Prolog, Smalltalk, Postscript, HTML, PERL, FORTRAN, Ada, COBOL, BASIC SNOBOL4, PL/I, Pascal. Begins with a background review of programming languages and the underlying hardware that will execute the given program; then covers the underlying grammatical model for programming languages and their compilers (elementary data types, data structures and encapsulation, inheritance, statements, procedure invocation, storage management, distributed processing, and network programming). Includes an advanced chapter on language semantics--program verification, denotational semantics, and the lambda calculus. For computer engineers and others interested in programming language designs.

Disruptive Possibilities: How Big Data Changes Everything


Jeffrey Needham - 2013
    As author Jeffrey Needham points out in this eye-opening book, big data can provide unprecedented insight into user habits, giving enterprises a huge market advantage. It will also inspire organizations to change the way they function."Disruptive Possibilities: How Big Data Changes Everything" takes you on a journey of discovery into the emerging world of big data, from its relatively simple technology to the ways it differs from cloud computing. But the big story of big data is the disruption of enterprise status quo, especially vendor-driven technology silos and budget-driven departmental silos. In the highly collaborative environment needed to make big data work, silos simply don't fit.Internet-scale computing offers incredible opportunity and a tremendous challenge--and it will soon become standard operating procedure in the enterprise. This book shows you what to expect.