This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    The book details the major subsystems and features of the Linux kernel, including its design, implementation, and interfaces. It covers the Linux kernel with both a practical and theoretical eye, which should appeal to readers with a variety of interests and needs. The author, a core kernel developer, shares valuable knowledge and experience on the 2.6 Linux kernel. Specific topics covered include process management, scheduling, time management and timers, the system call interface, memory addressing, memory management, the page cache, the VFS, kernel synchronization, portability concerns, and debugging techniques. This book covers the most interesting features of the Linux 2.6 kernel, including the CFS scheduler, preemptive kernel, block I/O layer, and I/O schedulers. The third edition of Linux Kernel Development includes new and updated material throughout the book:An all-new chapter on kernel data structuresDetails on interrupt handlers and bottom halvesExtended coverage of virtual memory and memory allocationTips on debugging the Linux kernelIn-depth coverage of kernel synchronization and lockingUseful insight into submitting kernel patches and working with the Linux kernel community

    

    Find out how the Swedish police combined XP, Scrum, and Kanban in a 60-person project. From start to finish, you'll see how to deliver a successful product using Lean principles. We start with an organization in desperate need of a new way of doing things and finish with a group of sixty, all working in sync to develop a scalable, complex system. You'll walk through the project step by step, from customer engagement, to the daily "cocktail party," version control, bug tracking, and release. In this honest look at what works--and what doesn't--you'll find out how to: Make quality everyone's business, not just the testers. Keep everyone moving in the same direction without micromanagement. Use simple and powerful metrics to aid in planning and process improvement. Balance between low-level feature focus and high-level system focus. You'll be ready to jump into the trenches and streamline your own development process.ContentsForewordPrefacePART I: HOW WE WORK1. About the Project1.1 Timeline 51.2 How We Sliced the Elephant 61.3 How We Involved the Customer 72. Structuring the Teams3. Attending the Daily Cocktail Party3.1 First Tier: Feature Team Daily Stand-up3.2 Second Tier: Sync Meetings per Specialty3.3 Third Tier: Project Sync Meeting4. The Project Board4.1 Our Cadences4.2 How We Handle Urgent Issues and Impediments5. Scaling the Kanban Boards6. Tracking the High-Level Goal7. Defining Ready and Done7.1 Ready for Development7.2 Ready for System Test7.3 How This Improved Collaboration 8. Handling Tech Stories8.1 Example 1: System Test Bottleneck8.2 Example 2: Day Before the Release8.3 Example 3: The 7-Meter Class9. Handling Bugs9.1 Continuous System Test9.2 Fix the Bugs Immediately9.3 Why We Limit the Number of Bugs in the Bug Tracker9.4 Visualizing Bugs9.5 Preventing Recurring Bugs10. Continuously Improving the Process10.1 Team Retrospectives10.2 Process Improvement Workshops10.3 Managing the Rate of Change11. Managing Work in Progress11.1 Using WIP Limits11.2 Why WIP Limits Apply Only to Features12. Capturing and Using Process Metrics12.1 Velocity (Features per Week)12.2 Why We Don’t Use Story Points12.3 Cycle Time (Weeks per Feature)12.4 Cumulative Flow12.5 Process Cycle Efficiency13. Planning the Sprint and Release13.1 Backlog Grooming13.2 Selecting the Top Ten Features13.3 Why We Moved Backlog Grooming Out of the Sprint Planning Meeting13.4 Planning the Release14. How We Do Version Control14.1 No Junk on the Trunk14.2 Team Branches14.3 System Test Branch15. Why We Use Only Physical Kanban Boards16. What We Learned16.1 Know Your Goal16.2 Experiment16.3 Embrace Failure16.4 Solve Real Problems16.5 Have Dedicated Change Agents16.6 Involve PeoplePART II: A CLOSER LOOK AT THE TECHNIQUES 17. Agile and Lean in a Nutshell17.1 Agile in a Nutshell17.2 Lean in a Nutshell17.3 Scrum in a Nutshell17.4 XP in a Nutshell17.5 Kanban in a Nutshell18. Reducing the Test Automation Backlog18.1 What to Do About It18.2 How to Improve Test Coverage a Little Bit Each Iteration18.3 Step 1: List Your Test Cases18.4 Step 2: Classify Each Test18.5 Step 3: Sort the List in Priority Order18.6 Step 4: Automate a Few Tests Each Iteration18.7 Does This Solve the Problem?19. Sizing the Backlog with Planning Poker19.1 Estimating Without Planning Poker19.2 Estimating with Planning Poker19.3 Special Cards20. Cause-Effect Diagrams20.1 Solve Problems, Not Symptoms20.2 The Lean Problem-Solving Approach: A3 Thinking20.3 How to Use Cause-Effect Diagrams20.4 Example 1: Long Release Cycle20.5 Example 2: Defects Released to Production20.6 Example 3: Lack of Pair Programming20.7 Example 4: Lots of Problems20.8 Practical Issues: How to Create and Maintain the Diagrams20.9 Pitfalls20.10 Why Use Cause-Effect Diagrams?21. Final WordsA1. Glossary: How We Avoid Buzzword BingoIndex

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

    Hadoop allowed small and medium sized companies to store huge amounts of data on cheap commodity servers in racks. The introduction of Big Data has allowed businesses to make decisions based on quantifiable analysis. Hadoop is now implemented in major organizations such as Amazon, IBM, Cloudera, and Dell to name a few. This book introduces you to Hadoop and to concepts such as ‘MapReduce’, ‘Rack Awareness’, ‘Yarn’ and ‘HDFS Federation’, which will help you get acquainted with the technology.

    This book is for the beginning to intermediate web developer who wants to solve web development problems with smart JavaScript. It does not assume any prior knowledge of JavaScript programming; however even if you already know some JavaScript, there will be plenty for you to learn here.

    There are no trite superlatives here. Packed with lessons learned from more than a decade of software development experience, author Ka Wai Cheung takes you through the programming profession from nearly every angle to uncover ways of sustaining a healthy connection with your work. You'll see how to stay productive even on the longest projects. You'll create a workflow that works with you, not against you. And you'll learn how to deal with clients whose goals don't align with your own. If you don't handle them just right, issues such as these can crush even the most seasoned, motivated developer. But with the right approach, you can transcend these common problems and become the professional developer you want to be. In more than 50 nuggets of wisdom, you'll learn: Why many traditional approaches to process and development roles in this industry are wrong - and how to sniff them out. Why you must always say "no" to the software pet project and open-ended timelines. How to incorporate code generation into your development process, and why its benefits go far beyond just faster code output. What to do when your client or end user disagrees with an approach you believe in. How to pay your knowledge forward to future generations of programmers through teaching and evangelism. If you're in this industry for the long run, you'll be coming back to this book again and again.

    This is one of those cases. The UNIX System Administration Handbook is one of the few books we ever measured ourselves against." -From the Foreword by Tim O'Reilly, founder of O'Reilly Media "This book is fun and functional as a desktop reference. If you use UNIX and Linux systems, you need this book in your short-reach library. It covers a bit of the systems' history but doesn't bloviate. It's just straightfoward information delivered in colorful and memorable fashion." -Jason A. Nunnelley"This is a comprehensive guide to the care and feeding of UNIX and Linux systems. The authors present the facts along with seasoned advice and real-world examples. Their perspective on the variations among systems is valuable for anyone who runs a heterogeneous computing facility." -Pat Parseghian The twentieth anniversary edition of the world's best-selling UNIX system administration book has been made even better by adding coverage of the leading Linux distributions: Ubuntu, openSUSE, and RHEL. This book approaches system administration in a practical way and is an invaluable reference for both new administrators and experienced professionals. It details best practices for every facet of system administration, including storage management, network design and administration, email, web hosting, scripting, software configuration management, performance analysis, Windows interoperability, virtualization, DNS, security, management of IT service organizations, and much more. UNIX(R) and Linux(R) System Administration Handbook, Fourth Edition, reflects the current versions of these operating systems: Ubuntu(R) LinuxopenSUSE(R) LinuxRed Hat(R) Enterprise Linux(R)Oracle America(R) Solaris(TM) (formerly Sun Solaris)HP HP-UX(R)IBM AIX(R)

    Tracy Kidder got a preview of this world in the late 1970s when he observed the engineers of Data General design and build a new 32-bit minicomputer in just one year. His thoughtful, prescient book, The Soul of a New Machine, tells stories of 35-year-old "veteran" engineers hiring recent college graduates and encouraging them to work harder and faster on complex and difficult projects, exploiting the youngsters' ignorance of normal scheduling processes while engendering a new kind of work ethic.These days, we are used to the "total commitment" philosophy of managing technical creation, but Kidder was surprised and even a little alarmed at the obsessions and compulsions he found. From in-house political struggles to workers being permitted to tease management to marathon 24-hour work sessions, The Soul of a New Machine explores concepts that already seem familiar, even old-hat, less than 20 years later. Kidder plainly admires his subjects; while he admits to hopeless confusion about their work, he finds their dedication heroic. The reader wonders, though, what will become of it all, now and in the future. —Rob Lightner

    Every integrated software development environment in the world--open-source, standards-based, and proprietary--now supports UML and, more importantly, the model-driven approach to software development. This makes learning the newest UML standard, UML 2.0, critical for all software developers--and there isn't a better choice than this clear, step-by-step guide to learning the language."--Richard Mark Soley, Chairman and CEO, OMGIf you're like most software developers, you're building systems that are increasingly complex. Whether you're creating a desktop application or an enterprise system, complexity is the big hairy monster you must manage.The Unified Modeling Language (UML) helps you manage this complexity. Whether you're looking to use UML as a blueprint language, a sketch tool, or as a programming language, this book will give you the need-to-know information on how to apply UML to your project. While there are plenty of books available that describe UML, Learning UML 2.0 will show you how to use it. Topics covered include:Capturing your system's requirements in your model to help you ensure that your designs meet your users' needsModeling the parts of your system and their relationshipsModeling how the parts of your system work together to meet your system's requirementsModeling how your system moves into the real world, capturing how your system will be deployedEngaging and accessible, this book shows you how to use UML to craft and communicate your project's design. Russ Miles and Kim Hamilton have written a pragmatic introduction to UML based on hard-earned practice, not theory. Regardless of the software process or methodology you use, this book is the one source you need to get up and running with UML 2.0.Russ Miles is a software engineer for General Dynamics UK, where he works with Java and Distributed Systems, although his passion at the moment is Aspect Orientation and, in particular, AspectJ. Kim Hamilton is a senior software engineer at Northrop Grumman, where she's designed and implemented a variety of systems including web applications and distributed systems, with frequent detours into algorithms development.

    As the size and complexity of commercial software have grown, the gap between academic computer science and industry has widened. It's an open secret that there is little engineering in software engineering, which continues to rely not on codified scientific knowledge but on intuition and experience.Barr, who worked as a programmer for more than twenty years, describes how the industry has evolved, from the era of mainframes and Fortran to today's embrace of the cloud. He explains bugs and why software has so many of them, and why today's interconnected computers offer fertile ground for viruses and worms. The difference between good and bad software can be a single line of code, and Barr includes code to illustrate the consequences of seemingly inconsequential choices by programmers. Looking to the future, Barr writes that the best prospect for improving software engineering is the move to the cloud. When software is a service and not a product, companies will have more incentive to make it good rather than "good enough to ship."

    They aren't conscious of all the choices they make, like how they format their source, the names they use for variables, or the kinds of loops they use. They're focused entirely on problems they're solving, solutions they're creating, and algorithms they're implementing. So they write code in the way that seems natural, that happens intuitively, and that feels good.But if you're serious about your profession, intuition isn't enough. Perl Best Practices author Damian Conway explains that rules, conventions, standards, and practices not only help programmers communicate and coordinate with one another, they also provide a reliable framework for thinking about problems, and a common language for expressing solutions. This is especially critical in Perl, because the language is designed to offer many ways to accomplish the same task, and consequently it supports many incompatible dialects.With a good dose of Aussie humor, Dr. Conway (familiar to many in the Perl community) offers 256 guidelines on the art of coding to help you write better Perl code--in fact, the best Perl code you possibly can. The guidelines cover code layout, naming conventions, choice of data and control structures, program decomposition, interface design and implementation, modularity, object orientation, error handling, testing, and debugging.They're designed to work together to produce code that is clear, robust, efficient, maintainable, and concise, but Dr. Conway doesn't pretend that this is the one true universal and unequivocal set of best practices. Instead, Perl Best Practices offers coherent and widely applicable suggestions based on real-world experience of how code is actually written, rather than on someone's ivory-tower theories on how software ought to be created.Most of all, Perl Best Practices offers guidelines that actually work, and that many developers around the world are already using. Much like Perl itself, these guidelines are about helping you to get your job done, without getting in the way.Praise for Perl Best Practices from Perl community members:"As a manager of a large Perl project, I'd ensure that every member of my team has a copy of Perl Best Practices on their desk, and use it as the basis for an in-house style guide." -- Randal Schwartz"There are no more excuses for writing bad Perl programs. All levels of Perl programmer will be more productive after reading this book." -- Peter Scott"Perl Best Practices will be the next big important book in the evolution of Perl. The ideas and practices Damian lays down will help bring Perl out from under the embarrassing heading of "scripting languages". Many of us have known Perl is a real programming language, worthy of all the tasks normally delegated to Java and C++. With Perl Best Practices, Damian shows specifically how and why, so everyone else can see, too." -- Andy Lester"Damian's done what many thought impossible: show how to build large, maintainable Perl applications, while still letting Perl be the powerful, expressive language that programmers have loved for years." -- Bill Odom"Finally, a means to bring lasting order to the process and product of real Perl development teams." -- Andrew Sundstrom"Perl Best Practices provides a valuable education in how to write robust, maintainable P

    You thought TDD was for someone else, but it's not! It's for you, the embedded C programmer. TDD helps you prevent defects and build software with a long useful life. This is the first book to teach the hows and whys of TDD for C programmers. TDD is a modern programming practice C developers need to know. It's a different way to program---unit tests are written in a tight feedback loop with the production code, assuring your code does what you think. You get valuable feedback every few minutes. You find mistakes before they become bugs. You get early warning of design problems. You get immediate notification of side effect defects. You get to spend more time adding valuable features to your product. James is one of the few experts in applying TDD to embedded C. With his 1.5 decades of training, coaching, and practicing TDD in C, C++, Java, and C# he will lead you from being a novice in TDD to using the techniques that few have mastered. This book is full of code written for embedded C programmers. You don't just see the end product, you see code and tests evolve. James leads you through the thought process and decisions made each step of the way. You'll learn techniques for test-driving code right next to the hardware, and you'll learn design principles and how to apply them to C to keep your code clean and flexible. To run the examples in this book, you will need a C/C++ development environment on your machine, and the GNU GCC tool chain or Microsoft Visual Studio for C++ (some project conversion may be needed).

    With this guide, pioneering Go programmer Mark Summerfield shows how to write code that takes full advantage of Go's breakthrough features and idioms. Both a tutorial and a language reference, "Programming in Go" brings together all the knowledge you need to evaluate Go, think in Go, and write high-performance software with Go. Summerfield presents multiple idiom comparisons showing exactly how Go improves upon older languages, calling special attention to Go's key innovations. Along the way, he explains everything from the absolute basics through Go's lock-free channel-based concurrency and its flexible and unusual duck-typing type-safe approach to object-orientation. Throughout, Summerfield's approach is thoroughly practical. Each chapter offers multiple live code examples designed to encourage experimentation and help you quickly develop mastery. Wherever possible, complete programs and packages are presented to provide realistic use cases, as well as exercises. Coverage includes:-- Quickly getting and installing Go, and building and running Go programs -- Exploring Go's syntax, features, and extensive standard library -- Programming Boolean values, expressions, and numeric types -- Creating, comparing, indexing, slicing, and formatting strings -- Understanding Go's highly efficient built-in collection types: slices and maps -- Using Go as a procedural programming language -- Discovering Go's unusual and flexible approach to object orientation -- Mastering Go's unique, simple, and natural approach to fine-grained concurrency -- Reading and writing binary, text, JSON, and XML files -- Importing and using standard library packages, custom packages, and third-party packages -- Creating, documenting, unit testing, and benchmarking custom packages