The Systems Bible: The Beginner's Guide to Systems Large and Small: Being the Third Edition of Systemantics


John Gall - 1977
    Hardcover published by Quadragle/The New York Times Book Co., third printing, August 1977, copyright 1975.

Functional Programming in Scala


Rúnar 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.

Hadoop: The Definitive Guide


Tom White - 2009
    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!

Managing Humans: Biting and Humorous Tales of a Software Engineering Manager


Michael Lopp - 2007
    Drawing on Lopp's management experiences at Apple, Netscape, Symantec, and Borland, this book is full of stories based on companies in the Silicon Valley where people have been known to yell at each other. It is a place full of dysfunctional bright people who are in an incredible hurry to find the next big thing so they can strike it rich and then do it all over again. Among these people are managers, a strange breed of people who through a mystical organizational ritual have been given power over your future and your bank account.Whether you're an aspiring manager, a current manager, or just wondering what the heck a manager does all day, there is a story in this book that will speak to you.

Agile Testing: A Practical Guide for Testers and Agile Teams


Lisa Crispin - 2008
    The widespread adoption of agile methods has brought the need for effective testing into the limelight, and agile projects have transformed the role of testers. Much of a tester's function, however, remains largely misunderstood. What is the true role of a tester? Do agile teams actually need members with QA backgrounds? What does it really mean to be an "agile tester?"Two of the industry's most experienced agile testing practitioners and consultants, Lisa Crispin and Janet Gregory, have teamed up to bring you the definitive answers to these questions and many others. In Agile Testing, Crispin and Gregory define agile testing and illustrate the tester's role with examples from real agile teams. They teach you how to use the agile testing quadrants to identify what testing is needed, who should do it, and what tools might help. The book chronicles an agile software development iteration from the viewpoint of a tester and explains the seven key success factors of agile testing.Readers will come away from this book understanding- How to get testers engaged in agile development- Where testers and QA managers fit on an agile team- What to look for when hiring an agile tester- How to transition from a traditional cycle to agile development- How to complete testing activities in short iterations- How to use tests to successfully guide development- How to overcome barriers to test automationThis book is a must for agile testers, agile teams, their managers, and their customers.

Deep Learning


Ian Goodfellow - 2016
    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Computer Systems: A Programmer's Perspective


Randal E. Bryant - 2002
    Often, computer science and computer engineering curricula don't provide students with a concentrated and consistent introduction to the fundamental concepts that underlie all computer systems. Traditional computer organization and logic design courses cover some of this material, but they focus largely on hardware design. They provide students with little or no understanding of how important software components operate, how application programs use systems, or how system attributes affect the performance and correctness of application programs. - A more complete view of systems - Takes a broader view of systems than traditional computer organization books, covering aspects of computer design, operating systems, compilers, and networking, provides students with the understanding of how programs run on real systems. - Systems presented from a programmers perspective - Material is presented in such a way that it has clear benefit to application programmers, students learn how to use this knowledge to improve program performance and reliability. They also become more effective in program debugging, because t

Land the Tech Job You Love


Andy Lester - 2008
    Your competition is smart, tech-savvy, and highly resourceful. Expectations among employers are higher. Your competition will run you over if you're not up to the challenge. Land the Tech Job You Love gives you the background, the skills, and the hard-won wisdom to bypass the mistakes of those who don't prepare. You might not think you need this book. Conventional Wisdom has it that finding a job is simple: send some resumes, go on some interviews, and take the offer that sounds best. But that's only the start. You've got the background and skills to work the Web and other resources that the general job seeker doesn't. This book shows you how to take advantage of those skills or be left behind by competing techies who do. It all starts with an examination of you, your strengths, and where you want your career to take you. Without a roadmap, you'll wind up in any old job. Life's too short to spend in a job that you don't love. From there, you'll see how to find the job you want that fits you and the employer, using your technical and web savvy to find the hidden jobs that never make it into the classifieds or Monster. "Marketing" is not a dirty word, and you'll learn how to present yourself, your skills, and your background in the way that shows the hiring company that you're the right person for the job. Create a resume that tosses out conventional wisdom, write cover letters that sell your background, and assemble a portfolio of work that will wow the interviewer. Social networking has been the darling of the Web in the past few years, but it's no substitute for the sort of personal interaction that makes relationships that help in future careers. As one manager said, "One recommendation is worth a million resumes." This book shows you how to make and maintain the connections that will drive your future career moves.Land the Tech Job You Love pulls no punches and lays out the details for what gets you an interview, and gets you hired in a job in the technical world that makes you happy.

The Tangled Web: A Guide to Securing Modern Web Applications


Michal Zalewski - 2011
    Every piece of the web application stack, from HTTP requests to browser-side scripts, comes with important yet subtle security consequences. To keep users safe, it is essential for developers to confidently navigate this landscape.In The Tangled Web, Michal Zalewski, one of the world's top browser security experts, offers a compelling narrative that explains exactly how browsers work and why they're fundamentally insecure. Rather than dispense simplistic advice on vulnerabilities, Zalewski examines the entire browser security model, revealing weak points and providing crucial information for shoring up web application security. You'll learn how to:Perform common but surprisingly complex tasks such as URL parsing and HTML sanitization Use modern security features like Strict Transport Security, Content Security Policy, and Cross-Origin Resource Sharing Leverage many variants of the same-origin policy to safely compartmentalize complex web applications and protect user credentials in case of XSS bugs Build mashups and embed gadgets without getting stung by the tricky frame navigation policy Embed or host user-supplied content without running into the trap of content sniffing For quick reference, "Security Engineering Cheat Sheets" at the end of each chapter offer ready solutions to problems you're most likely to encounter. With coverage extending as far as planned HTML5 features, The Tangled Web will help you create secure web applications that stand the test of time.

The Well-Grounded Java Developer: Vital techniques of Java 7 and polyglot programming


Benjamin J. Evans - 2012
    New JVM-based languages like Groovy, Scala, and Clojure are redefining what it means to be a Java developer. The core Standard and Enterprise APIs now co-exist with a large and growing body of open source technologies. Multicore processors, concurrency, and massive data stores require new patterns and approaches to development. And with Java 7 due to release in 2011, there's still more to absorb.The Well-Grounded Java Developer is a unique guide written for developers with a solid grasp of Java fundamentals. It provides a fresh, practical look at new Java 7 features along with the array of ancillary technologies that a working developer will use in building the next generation of business software.

Security Engineering: A Guide to Building Dependable Distributed Systems


Ross J. Anderson - 2008
    Spammers, virus writers, phishermen, money launderers, and spies now trade busily with each other in a lively online criminal economy and as they specialize, they get better. In this indispensable, fully updated guide, Ross Anderson reveals how to build systems that stay dependable whether faced with error or malice. Here's straight talk on critical topics such as technical engineering basics, types of attack, specialized protection mechanisms, security psychology, policy, and more.

Learning React Native: Building Native Mobile Apps with JavaScript


Bonnie Eisenman - 2016
    With this hands-on guide, you'll learn how to build applications that target iOS, Android, and other mobile platforms instead of browsers. You'll also discover how to access platform features such as the camera, user location, and local storage.With code examples and step-by-step instructions, author Bonnie Eisenman shows web developers and frontend engineers how to build and style interfaces, use mobile components, and debug and deploy apps. Along the way, you'll build several increasingly sophisticated sample apps with React Native before putting everything together at the end.Learn how React Native provides an interface to native UI componentsExamine how the framework uses native components analogous to HTML elementsCreate and style your own React Native components and applicationsInstall modules for APIs and features not supported by the frameworkGet tools for debugging your code, and for handling issues outside of JavaScriptPut it all together with the Zebreto effective-memorization flashcard appDeploy apps to the iOS App Store and Google's Play Store

Python Cookbook


David Beazley - 2002
    Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.Topics include:Data Structures and AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions

Learning XML


Erik T. Ray - 2001
    Fortunately, there s a solution: Erik T. Ray s Learning XML, Second Edition. This book presents an outstanding birds-eye view of the XML landscape. It s definitely not a programming book (though it does introduce some key XML programming issues). Rather, it s focused on key ideas you need to understand whatever you want to do with XML. That could be document management, web or print content delivery, application integration, B2B commerce, data storage, internationalization -- you name it.Ray s day job is software developer and XML specialist at O Reilly. There, he s helped to implement a complete publishing solution, using DocBook-XML and Perl to produce books in print, on CD-ROM, and for online delivery. So he understands XML from the real-world point of view of someone with a job to do. His first goal is to take on the big questions. First, What is XML? Ray attacks this question from multiple angles, introducing XML as a general-purpose information storage system, a markup language toolkit, and an open standard (or, increasingly, a collection of standards). What can (and can t) you do with XML? What s the history that led us here? And what tools do you need to get started? Next, he introduces the basic building blocks of XML markup and all XML-derived languages: stuff you ll need to know regardless of your goals. Through easy examples, you ll understand elements, attributes, entities, and processing instructions -- and how they fit together in a well-formed XML document. Then, it s on to representing information with XML -- in other words, understanding the nature and planning the structure of the documents you ll be using. Ray starts simply, then builds on his basic examples to discuss narrative documents with text flows, block and inline elements, and titled sections. Once you can handle those, he discusses more complex information modeling, as used in specialized markup languages such as VML. This edition contains an entirely new chapter on XML Schemas -- what he calls the shepherds that keep documents from straying outside of the herd and causing trouble. Schemas, of course, have become hugely important. This is one of the best plain-English introductions to the topic we ve seen. Ray then turns to presentation, introducing CSS stylesheets, basic usage, rule matching, properties, and more. A little later on, he returns to the subject -- this time with a complete introduction to XSL-FO that illuminates two powerful examples. The first is TEI-XML, a markup language for scholarly documents (Ray presents a Shakespearean sonnet, appropriately coded). The second is the immensely powerful DocBook -- which, as we ve observed, Ray knows inside and out. Learning XML is superbly written. Clear explanations. Simple examples. Great metaphors and analogies. And excellent introductions to nearly every topic that matters, from links to presentation, transformation to internationalization. If you re just starting out with XML, you re lucky to have it. Bill CamardaBill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks for Dummies, Second Edition.

Python for Data Analysis


Wes McKinney - 2011
    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples