Douglas Hubbard helps us create a path to know the answer to almost any question in business, in science, or in life . . . Hubbard helps us by showing us that when we seek metrics to solve problems, we are really trying to know something better than we know it now. How to Measure Anything provides just the tools most of us need to measure anything better, to gain that insight, to make progress, and to succeed." -Peter Tippett, PhD, M.D. Chief Technology Officer at CyberTrust and inventor of the first antivirus software "Doug Hubbard has provided an easy-to-read, demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions. We encourage our clients to try his powerful, practical techniques." -Peter Schay EVP and COO of The Advisory Council "As a reader you soon realize that actually everything can be measured while learning how to measure only what matters. This book cuts through conventional cliches and business rhetoric and offers practical steps to using measurements as a tool for better decision making. Hubbard bridges the gaps to make college statistics relevant and valuable for business decisions." -Ray Gilbert EVP Lucent "This book is remarkable in its range of measurement applications and its clarity of style. A must-read for every professional who has ever exclaimed, 'Sure, that concept is important, but can we measure it?'" -Dr. Jack Stenner Cofounder and CEO of MetraMetrics, Inc.

    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

    The term 'hacker' has been redefined to consist of anyone who has an insatiable curiosity as to how things work--and how they can try to make them better. This book is aimed at hackers of all skill levels and explains the classical principles and techniques behind beautiful designs by deconstructing those designs in order to understand what makes them so remarkable. Author and designer David Kadavy provides you with the framework for understanding good design and places a special emphasis on interactive mediums. You'll explore color theory, the role of proportion and geometry in design, and the relationship between medium and form. Packed with unique reverse engineering design examples, this book inspires and encourages you to discover and create new beauty in a variety of formats. Breaks down and studies the classical principles and techniques behind the creation of beautiful design. Illustrates cultural and contextual considerations in communicating to a specific audience. Discusses why design is important, the purpose of design, the various constraints of design, and how today's fonts are designed with the screen in mind. Dissects the elements of color, size, scale, proportion, medium, and form. Features a unique range of examples, including the graffiti in the ancient city of Pompeii, the lack of the color black in Monet's art, the style and sleekness of the iPhone, and more.By the end of this book, you'll be able to apply the featured design principles to your own web designs, mobile apps, or other digital work.

    Abbott and Michael T. Fisher cover everything IT and business leaders must know to build technology infrastructures that can scale smoothly to meet any business requirement. Drawing on their unparalleled experience managing some of the world s highest-transaction-volume Web sites, the authors provide detailed models and best-practice approaches available in no other book. Unlike previous books on scalability, "The Art of Scalability" doesn t limit its coverage to technology. Writing for both technical and nontechnical decision-makers, this book covers everything that impacts scalability, including architecture, processes, people, and organizations. Throughout, the authors address a broad spectrum of real-world challenges, from performance testing to IT governance. Using their tools and guidance, organizations can systematically overcome obstacles to scalability and achieve unprecedented levels of technical and business performance. Coverage includes Staffing the scalable organization: essential organizational, management, and leadership skills for technical leaders Building processes for scale: process lessons from hyper-growth companies, from technical issue resolution to crisis management Making better build versus buy decisions Architecting scalable solutions: powerful proprietary models for identifying scalability needs and choosing the best approaches to meet them Optimizing performance through caching, application and database splitting, and asynchronous design Scalability techniques for emerging technologies, including clouds and grids Planning for rapid data growth and new data centers Evolving monitoring strategies to tightly align with customer requirements "

    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

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    We’re building more products than ever before, but most of them fail—not because we can’t complete what we set out to build, but because we waste time, money, and effort building the wrong product.What we need is a systematic process for quickly vetting product ideas and raising our odds of success. That’s the promise of Running Lean.In this inspiring book, Ash Maurya takes you through an exacting strategy for achieving a "product/market fit" for your fledgling venture, based on his own experience in building a wide array of products from high-tech to no-tech. Throughout, he builds on the ideas and concepts of several innovative methodologies, including the Lean Startup, Customer Development, and bootstrapping.Running Lean is an ideal tool for business managers, CEOs, small business owners, developers and programmers, and anyone who’s interested in starting a business project.Find a problem worth solving, then define a solutionEngage your customers throughout the development cycleContinually test your product with smaller, faster iterationsBuild a feature, measure customer response, and verify/refute the ideaKnow when to "pivot" by changing your plan’s courseMaximize your efforts for speed, learning, and focusLearn the ideal time to raise your "big round" of fundingGet on track with The Lean Series Presented by Eric Ries—bestselling author of The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses—The Lean Series gives you solid footing in a proven methodology that will help your business succeed.

    The blades start moving in 60 seconds. What do you do? If you want to work at Google, or any of America's best companies, you need to have an answer to this and other puzzling questions. Are You Smart Enough to Work at Google? guides readers through the surprising solutions to dozens of the most challenging interview questions. The book covers the importance of creative thinking, ways to get a leg up on the competition, what your Facebook page says about you, and much more. Are You Smart Enough to Work at Google? is a must-read for anyone who wants to succeed in today's job market.

    Aging computer systems present complex technical challenges for organizations both large and small, and Kill It with Fire provides sound strategies for spearheading modernization efforts.Kill It with Fire examines aging computer systems, the evolution of technology over time, and how organizations can modernize, maintain, and future-proof their current systems.In playful and engaging prose, Marianne Bellotti uses real-world case studies to illustrate the technical challenges of modernizing complex legacy systems, as well as the organizational challenges of time-intensive maintenance efforts. The book explains how to evaluate existing architecture, create upgrade plans, and handle communication structures. Team exercises and historical analyses of complex computer systems make this a valuable resource for those in both older and newer companies, and will help readers restore or create systems built to evolve as time goes on.

    More than a series of fascinating case studies, To Engineer Is Human is a work that looks at our deepest notions of progress and perfection, tracing the fine connection between the quantifiable realm of science and the chaotic realities of everyday life."Alert, inquisitive, unspecialized, wholly human...refreshingly eclectic." --The Spectator"Henry Petroski is an ardent engineer, and if he writes more good books like this, he might find himself nominated to become the meistersinger of the guild. [This is] a refreshing plunge into the dynamics of the engineering ethos...as straightforward as an I-beam."--Science

    His walk through the syntax and semantics of JavaScript is both charming and hugely insightful; reminders of gotchas complement realistic use cases, paced at a comfortable curve. You'll find when you finish the book that you've gained a strong and comprehensive sense of mastery." --Paul Irish, developer advocate, Google Chrome "This is not a book for those looking for shortcuts; rather it is hard-won experience distilled into a guided tour. It's one of the few books on JS that I'll recommend without hesitation." --Alex Russell, TC39 member, software engineer, Google In order to truly master JavaScript, you need to learn how to work effectively with the language's flexible, expressive features and how to avoid its pitfalls. No matter how long you've been writing JavaScript code, Effective JavaScript will help deepen your understanding of this powerful language, so you can build more predictable, reliable, and maintainable programs. Author David Herman, with his years of experience on Ecma's JavaScript standardization committee, illuminates the language's inner workings as never before--helping you take full advantage of JavaScript's expressiveness. Reflecting the latest versions of the JavaScript standard, the book offers well-proven techniques and best practices you'll rely on for years to come. Effective JavaScript is organized around 68 proven approaches for writing better JavaScript, backed by concrete examples. You'll learn how to choose the right programming style for each project, manage unanticipated problems, and work more successfully with every facet of JavaScript programming from data structures to concurrency. Key features include Better ways to use prototype-based object-oriented programming Subtleties and solutions for working with arrays and dictionary objects Precise and practical explanations of JavaScript's functions and variable scoping semantics Useful JavaScript programming patterns and idioms, such as options objects and method chaining In-depth guidance on using JavaScript's unique "run-to-completion" approach to concurrency

    The pass was intercepted and the Seahawks lost. Critics called it the dumbest play in history. But was the call really that bad? Or did Carroll actually make a great move that was ruined by bad luck?Even the best decision doesn't yield the best outcome every time. There's always an element of luck that you can't control, and there is always information that is hidden from view. So the key to long-term success (and avoiding worrying yourself to death) is to think in bets: How sure am I? What are the possible ways things could turn out? What decision has the highest odds of success? Did I land in the unlucky 10% on the strategy that works 90% of the time? Or is my success attributable to dumb luck rather than great decision making?Annie Duke, a former World Series of Poker champion turned business consultant, draws on examples from business, sports, politics, and (of course) poker to share tools anyone can use to embrace uncertainty and make better decisions. For most people, it's difficult to say "I'm not sure" in a world that values and, even, rewards the appearance of certainty. But professional poker players are comfortable with the fact that great decisions don't always lead to great outcomes and bad decisions don't always lead to bad outcomes.By shifting your thinking from a need for certainty to a goal of accurately assessing what you know and what you don't, you'll be less vulnerable to reactive emotions, knee-jerk biases, and destructive habits in your decision making. You'll become more confident, calm, compassionate and successful in the long run.

    This makes the book random-access: Items are easy to browse and study in whatever order the reader needs. I will be recommending "Effective Python" to students as an admirably compact source of mainstream advice on a very broad range of topics for the intermediate Python programmer. " Brandon Rhodes, software engineer at Dropbox and chair of PyCon 2016-2017" It s easy to start coding with Python, which is why the language is so popular. However, Python s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. " Effective Python " will help you master a truly Pythonic approach to programming, harnessing Python s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers best-selling "Effective C++, " Brett Slatkin brings together 59 Python best practices, tips, and shortcuts, and explains them with realistic code examples. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You ll learn the best way to accomplish key tasks, so you can write code that s easier to understand, maintain, and improve. Key features includeActionable guidelines for all major areas of Python 3.x and 2.x development, with detailed explanations and examples Best practices for writing functions that clarify intention, promote reuse, and avoid bugs Coverage of how to accurately express behaviors with classes and objects Guidance on how to avoid pitfalls with metaclasses and dynamic attributes More efficient approaches to concurrency and parallelism Better techniques and idioms for using Python s built-in modules Tools and best practices for collaborative development Solutions for debugging, testing, and optimization in order to improve quality and performance "

    The story of information begins in a time profoundly unlike our own, when every thought and utterance vanishes as soon as it is born. From the invention of scripts and alphabets to the long-misunderstood talking drums of Africa, Gleick tells the story of information technologies that changed the very nature of human consciousness. He provides portraits of the key figures contributing to the inexorable development of our modern understanding of information: Charles Babbage, the idiosyncratic inventor of the first great mechanical computer; Ada Byron, the brilliant and doomed daughter of the poet, who became the first true programmer; pivotal figures like Samuel Morse and Alan Turing; and Claude Shannon, the creator of information theory itself. And then the information age arrives. Citizens of this world become experts willy-nilly: aficionados of bits and bytes. And we sometimes feel we are drowning, swept by a deluge of signs and signals, news and images, blogs and tweets. The Information is the story of how we got here and where we are heading.

    Be part of the solution. With this practical book, you'll learn 10 easy-to-follow guidelines for delivering software that's easy to maintain and adapt. These guidelines have been derived from analyzing hundreds of real-world systems.Written by consultants from the Software Improvement Group (SIG), this book provides clear and concise explanations, with advice for turning the guidelines into practice. Examples are written in Java, but this guide is equally useful for developers working in other programming languages.10 Coding Guidelines- Write short units of code: limit the length of methods and constructors- Write simple units of code: limit the number of branch points per method- Write code once, rather than risk copying buggy code- Keep unit interfaces small by extracting parameters into objects- Separate concerns to avoid building large classes- Couple architecture components loosely- Balance the number and size of top-level components in your code- Keep your codebase as small as possible- Automate tests for your codebase- Write clean code, avoiding "code smells" that indicate deeper problemsWhy you should read this bookTaken in isolation, the guidelines presented in this book are well-known. In fact, many well-known tools for code analysis check a number of the guidelines presented here. The following three characteristics set this book apart from other books on software development: We have selected the ten most important guidelines from experience.We teach how to comply with these ten guidelines.We present statistics and examples from real-world systems.This book is part our Training on Software Maintainability - and subsequent Certification on Quality Software Development program. For more information about this program, please contact training@sig.eu.