His factory is rapidly heading for disaster. So is his marriage. He has ninety days to save his plant—or it will be closed by corporate HQ, with hundreds of job losses. It takes a chance meeting with a colleague from student days—Jonah—to help him break out of conventional ways of thinking to see what needs to be done.The story of Alex's fight to save his plant is more than compulsive reading. It contains a serious message for all managers in industry and explains the ideas which underline the Theory of Constraints (TOC) developed by Eli Goldratt.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Learn You a Haskell for Great Good! introduces programmers familiar with imperative languages (such as C++, Java, or Python) to the unique aspects of functional programming. Packed with jokes, pop culture references, and the author's own hilarious artwork, Learn You a Haskell for Great Good! eases the learning curve of this complex language, and is a perfect starting point for any programmer looking to expand his or her horizons. The well-known web tutorial on which this book is based is widely regarded as the best way for beginners to learn Haskell, and receives over 30,000 unique visitors monthly.

    This practical guide provides application developers, sysadmins, and DevOps practitioners with a hands-on introduction to the most important aspects of Prometheus, including dashboarding and alerting, direct code instrumentation, and metric collection from third-party systems with exporters.This open source system has gained popularity over the past few years for good reason. With its simple yet powerful data model and query language, Prometheus does one thing, and it does it well. Author and Prometheus developer Brian Brazil guides you through Prometheus setup, the Node exporter, and the Alertmanager, then demonstrates how to use them for application and infrastructure monitoring.Know where and how much to apply instrumentation to your application codeIdentify metrics with labels using unique key-value pairsGet an introduction to Grafana, a popular tool for building dashboardsLearn how to use the Node Exporter to monitor your infrastructureUse service discovery to provide different views of your machines and servicesUse Prometheus with Kubernetes and examine exporters you can use with containersConvert data from other monitoring systems into the Prometheus format

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    And it’s still short, profusely illustrated…and best of all–fun to read.If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites.

    This book explains the technical aspects of hacking, including stack based overflows, heap based overflows, string exploits, return-into-libc, shellcode, and cryptographic attacks on 802.11b.

    Today, twenty million people worldwide are surfing the Net. Where Wizards Stay Up Late is the exciting story of the pioneers responsible for creating the most talked about, most influential, and most far-reaching communications breakthrough since the invention of the telephone. In the 1960's, when computers where regarded as mere giant calculators, J.C.R. Licklider at MIT saw them as the ultimate communications devices. With Defense Department funds, he and a band of visionary computer whizzes began work on a nationwide, interlocking network of computers. Taking readers behind the scenes, Where Wizards Stay Up Late captures the hard work, genius, and happy accidents of their daring, stunningly successful venture.

    The tools and recipes in this book will help you uncover and solve hidden (and not-so-hidden) problems with your technology, your methodology, and those difficult "people" issues on your team.Project retrospectives help teams examine what went right and what went wrong on a project. But traditionally, retrospectives (also known as "post-mortems") are only helpful at the end of the project--too late to help. You need agile retrospectives that are iterative and incremental. You need to accurately find and fix problems to help the team today.Now, Derby and Larsen show you the tools, tricks, and tips you need to fix the problems you face on a software development project on an on-going basis. You'll see how to architect retrospectives in general, how to design them specifically for your team and organization, how to run them effectively, how to make the needed changes, and how to scale these techniques up. You'll learn how to deal with problems, and implement solutions effectively throughout the project--not just at the end.With regular tune-ups, your team will hum like a precise, world-class orchestra.ContentsForwardPrefaceIntroduction1. Helping your team inspect and adapt2. A retrospective custom-fit for your team3. Leading retrospectives4. Activities to set the stage5. Activities to gather data6. Activities to gather insights7. Activities to decide what to do8. Activities to close the retrospective9. Releases and project retrospectives10. Make it soA1. Facilitation suppliesA2. Debriefing activitiesA3. Activities quick reference matrixA4. Resources for learning facilitation skillsA5. Bibliography

    By applying the design patterns outlined in this book, you’ll learn how to write flexible and resilient code that’s easier—not harder—to work with as your code base grows.JavaScript has become one of the most widely used—and essential—programming languages for the Web, on both the client-side and server-side. In the real world, JavaScript applications are fragile, and when you change them things often break. Author Eric Elliott shows you how to add features without creating bugs or negatively impacting the rest of your code during the course of building a large JavaScript application.Examine the anatomy of a modern JavaScript applicationLearn best practices for code organization, modularity, and reuseApply Model-View-Controller architectures to client-side web developmentDelve into client-side (browser) and server-side (Node) approachesUse Node to design and program RESTful APIsLearn the processes teams use to build, test, deploy, and scale large JavaScript applicationsExpand your application’s reach through platform targets and internationalization

     Leading-edge companies like Amazon and Google are applying DevOps and Agile principles to deliver large software projects faster than anyone thought possible. But most executives don’t understand how to transform their current legacy systems and processes to scale these principles across their organizations. Leading the Transformation is an executive guide, providing a clear framework for improving development and delivery. Instead of the traditional Agile and DevOps approaches that focus on improving the effectiveness of teams, this book targets the coordination of work across teams in large organizations—an improvement that executives are uniquely positioned to lead.

    The meaning of the business process diagram is the same, regardless of the tool used to create it. But creating models that are correct, complete, and clear demands more than a dictionary of BPMN shapes and symbols. It also requires a methodology for translating process logic consistently into the diagram. And it requires a measure of modeling style as well, conventions that ensure that the process logic is unambiguous from the diagram by itself. In short, "good BPMN" requires a disciplined approach called "method and style."In this book, Bruce Silver explains which BPMN elements process modelers need to understand, in two levels, including exactly where and how to use each element. Level 1 (the Descriptive modeling subclass of BPMN 2.0) is a palette of shapes and symbols largely carried over from traditional flowcharting. Level 2 (the Analytic subclass) expands the palette to be able to describe event-triggered behavior, critical to modeling exception handling.The book explains the real meaning of BPMN's most basic concepts - like activity, process, and end state - essential to using the language correctly, and provides a step-by-step methodology for going from a blank page to a complete end-to-end BPMN model, developed from the top down in a hierarchical structure. From the top-level diagram you can see on a single page exactly how the process starts, its possible end states, what the instance represents, and communications with the Customer, service providers, and other processes. From there you can drill down to see the details of any part of the process. Thie popular first edition of this book was published in 2009 based on the draft BPMN 2.0 specification. This second edition is based on the final BPMN 2.0 specification. Although the diagram elements have changed little since the first edition, both the methodology and style sections have been completely rewritten.The second half of the book, the BPMN Implementer's Guide, is completely new. It puts the focus on the XML serialization of the diagram, for both non-executable and executable process models. It details the BPMN 2.0 metamodel and XML Schema, and describes the BPMN-I Profile, a set of serialization rules that facilitate interchange of BPMN models in the Analytic subclass between tools. It also explains how BPMN 2.0 describes execution-related details, such as process data and data mapping, services, messages, and human task assignment, illustrated with an example executable process created in Bonita Open Solution. It concludes with guidelines for implementers on how to align executable design with business-oriented top-down process modeling.The book is lavishly illustrated with over 100 BPMN diagrams, and the BPMN Implementer's Guide section contains many XML examples as well.Bruce Silver is the leading provider of BPMN training and certification. He has been providing BPMN training since early 2007 and is regarded as an authority in the field.

    Based on numerous interviews, this book reveals exclusive new information about how Apple innovates, deals with its suppliers, and is handling the transition into the post Jobs era.

     Test-Driven JavaScript Development is a complete, best-practice guide to agile JavaScript testing and quality assurance with the test-driven development (TDD) methodology. Leading agile JavaScript developer Christian Johansen covers all aspects of applying state-of-the-art automated testing in JavaScript environments, walking readers through the entire development lifecycle, from project launch to application deployment, and beyond.Using real-life examples driven by unit tests, Johansen shows how to use TDD to gain greater confidence in your code base, so you can fearlessly refactor and build more robust, maintainable, and reliable JavaScript code at lower cost. Throughout, he addresses crucial issues ranging from code design to performance optimization, offering realistic solutions for developers, QA specialists, and testers.Coverage includes - Understanding automated testing and TDD - Building effective automated testing workflows - Testing code for both browsers and servers (using Node.js) - Using TDD to build cleaner APIs, better modularized code, and more robust software - Writing testable code - Using test stubs and mocks to test units in isolation - Continuously improving code through refactoring - Walking through the construction and automated testing of fully functional softwareThe accompanying Web site, tddjs.com, contains all of the book's code listings and additional resources.