Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer winning in games like Jeopardy and go does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules. These approaches are too narrow to achieve genuine intelligence. The world we live in is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Marcus and Davis show us what we need to first accomplish before we get there and argue that if we are wise along the way, we won't need to worry about a future of machine overlords. If we heed their advice, humanity can create an AI that we can trust in our homes, our cars, and our doctor's offices. Reboot provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of what we can achieve and how AI can make our lives better.

    It discusses new results, along with applications of probability theory to a variety of problems. The book contains many exercises and is suitable for use as a textbook on graduate-level courses involving data analysis. Aimed at readers already familiar with applied mathematics at an advanced undergraduate level or higher, it is of interest to scientists concerned with inference from incomplete information.

    But many managers can't read a balance sheet, wouldn't recognize a liquidity ratio, and don't know how to calculate return on investment. Worse, they don't have any idea where the numbers come from or how reliable they really are. In Financial Intelligence, Karen Berman and Joe Knight teach the basics of finance--but with a twist. Financial reporting, they argue, is as much art as science. Because nobody can quantify everything, accountants always rely on estimates, assumptions, and judgment calls. Savvy managers need to know how those sources of possible bias can affect the financials and that sometimes the numbers can be challenged. While providing the foundation for a deep understanding of the financial side of business, the book also arms managers with practical strategies for improving their companies' performance--strategies, such as "managing the balance sheet," that are well understood by financial professionals but rarely shared with their nonfinancial colleagues. Accessible, jargon-free, and filled with entertaining stories of real companies, Financial Intelligence gives nonfinancial managers the financial knowledge and confidence for their everyday work. Karen Berman and Joe Knight are the owners of the Los Angeles-based Business Literacy Institute and have trained tens of thousands of managers at many leading organizations. Co-author John Case has written several popular books on management.

    The Unwritten Laws of Business is such a book. Originally published over 60 years ago as The Unwritten Laws of Engineering, it has sold over 100,000 copies, despite the fact that it has never been available before to general readers. Fully revised for business readers today, here are but a few of the gems you’ll find in this little-known business classic: If you take care of your present job well, the future will take care of itself.The individual who says nothing is usually credited with having nothing to say.Whenever you are performing someone else’s function, you are probably neglecting your own.Martyrdom only rarely makes heroes, and in the business world, such heroes and martyrs often find themselves unemployed.Refreshingly free of the latest business fads and jargon, this is a book that is wise and insightful, capturing and distilling the timeless truths and principles that underlie management and business the world over.The little book with the big history.In the summer of 2005, Business 2.0 published a cover story on Raytheon CEO William Swanson’s self-published pamphlet, Swanson’s Unwritten Rules of Management. Lauded by such chief executives as Jack Welch and Warren Buffett, the booklet becamea quiet phenomenon. As it turned out, much of Swanson’s book drew from a classic of business literature that has been in print for more than sixty years. Now, in a new edition revised and updated for business readers today, we are reissuing the 1944 classic that inspired a number of Swanson’s “rules”: The Unwritten Laws of Business. Filled with sage advice and written in a spare, engaging style, The Unwritten Laws of Business offers insights on working with others, reporting to a boss, organizing a project, running a meeting, advancing your career, and more. Here’s just a sprinkling of the old-fashioned, yet surprisingly relevant, wisdom you’ll find in these pages:If you have no intention of listening to, considering, and perhaps using, someone’s opinion, don’t ask for it.Count any meeting a failure that does not end up with a definite understanding as to what’s going to be done, who’s going to do it, and when.The common belief that everyone can do anything if they just try hard enough is a formula for inefficiency at best and for complete failure at worst.It is natural enough to “look out for Number One first,” but when you do, your associates will be noticeably disinclined to look out for you.Whether you’re a corporate neophyte or seasoned manager, this charming book reveals everything you need to know about the “unwritten” laws of business.

    Never again will you order the Poisson Distribution in a French restaurant!This updated version features all new material.

    Just set aside one hour a day—lunchtime would be perfect—for a month, and you'll be automating Windows tasks faster than you ever thought possible. You'll start with the basics—what is PowerShell and what can you do with it. Then, you'll move systematically through the techniques and features you'll use to make your job easier and your day shorter. This totally revised second edition covers new PowerShell 3 features designed for Windows 8 and Windows Server 2012.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.What's InsideLearn PowerShell from the beginning—no experience required! Covers PowerShell 3, Windows 8, and Windows Server 2012 Each lesson should take you one hour or lessAbout the TechnologyPowerShell is both a language and an administrative shell with which you can control and automate nearly every aspect of Windows. It accepts and executes commands immediately, and you can write scripts to manage most Windows servers like Exchange, IIS, and SharePoint.Experience with Windows administration is helpful. No programming experience is assumed.Table of ContentsBefore you begin Meet PowerShell Using the help system Running commands Working with providers The pipeline: connecting commands Adding commands Objects: data by another name The pipeline, deeper Formatting—and why it's done on the right Filtering and comparisons A practical interlude Remote control: one to one, and one to many Using Windows Management Instrumentation Multitasking with background jobs Working with many objects, one at a time Security alert! Variables: a place to store your stuff Input and output Sessions: remote control with less work You call this scripting? Improving your parameterized script Advanced remoting configuration Using regular expressions to parse text files Additional random tips, tricks, and techniques Using someone else's script Never the end PowerShell cheat sheet

    But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You'll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization's goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures

    It also covers MySQL, and PostgreSQL. It contains examples which have been tested against each SQL platform, with incompatibilities or platform distinctives called out and explained.

    Its broad appeal lies in its interactive environment with hundreds of built-in functions for technical computation, graphics, and animation. In addition, it provides easy extensibility with its own high-level programming language. Enhanced by fun and appealing illustrations, Getting Started with MATLAB 7: A Quick Introduction for Scientists and Engineers employs a casual, accessible writing style that shows users how to enjoy using MATLAB.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok.In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the human obsessions surrounding it. She traces its discovery by an amateur mathematician in the 1740s through its development into roughly its modern form by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—at the same time that practitioners relied on it to solve crises involving great uncertainty and scanty information (Alan Turing's role in breaking Germany's Enigma code during World War II), and explains how the advent of off-the-shelf computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security.Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time.

    Edited by the Sustainability Institute’s Diana Wright, this essential primer brings systems thinking out of the realm of computers and equations and into the tangible world, showing readers how to develop the systems-thinking skills that thought leaders across the globe consider critical for 21st-century life.Some of the biggest problems facing the world—war, hunger, poverty, and environmental degradation—are essentially system failures. They cannot be solved by fixing one piece in isolation from the others, because even seemingly minor details have enormous power to undermine the best efforts of too-narrow thinking.While readers will learn the conceptual tools and methods of systems thinking, the heart of the book is grander than methodology. Donella Meadows was known as much for nurturing positive outcomes as she was for delving into the science behind global dilemmas. She reminds readers to pay attention to what is important, not just what is quantifiable, to stay humble, and to stay a learner.In a world growing ever more complicated, crowded, and interdependent, Thinking in Systems helps readers avoid confusion and helplessness, the first step toward finding proactive and effective solutions.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    These very real results were achieved through learning the management techniques that spell profitability for the organization and its employees.The One Minute Manager is a concise, easily read story that reveals three very practical secrets: One Minute Goals, One Minute Praisings, and One Minute Reprimands. The audio also presents several studies in medicine and the behavioral sciences that clearly explain why these apparently simple methods work so well with so many people. By the audio's end you will know how to apply them to your own situation and enjoy the benefits.

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!