In an Internet society, according to Richard Susskind and Daniel Susskind, we will neither need nor want doctors, teachers, accountants, architects, the clergy, consultants, lawyers, and many others, to work as they did in the 20th century.The Future of the Professions explains how 'increasingly capable systems' -- from telepresence to artificial intelligence -- will bring fundamental change in the way that the 'practical expertise' of specialists is made available in society.The authors challenge the 'grand bargain' -- the arrangement that grants various monopolies to today's professionals. They argue that our current professions are antiquated, opaque and no longer affordable, and that the expertise of their best is enjoyed only by a few. In their place, they propose six new models for producing and distributing expertise in society.The book raises important practical and moral questions. In an era when machines can out-perform human beings at most tasks, what are the prospects for employment, who should own and control online expertise, and what tasks should be reserved exclusively for people?Based on the authors' in-depth research of more than ten professions, and illustrated by numerous examples from each, this is the first book to assess and question the relevance of the professions in the 21st century.

    The title says it is the hard way to learn to writecode but it’s actually not. It’s the “hard” way only in that it’s the way people used to teach things. In this book youwill do something incredibly simple that all programmers actually do to learn a language: 1. Go through each exercise. 2. Type in each sample exactly. 3. Make it run.That’s it. This will be very difficult at first, but stick with it. If you go through this book, and do each exercise for1-2 hours a night, then you’ll have a good foundation for moving on to another book. You might not really learn“programming” from this book, but you will learn the foundation skills you need to start learning the language.This book’s job is to teach you the three most basic essential skills that a beginning programmer needs to know:Reading And Writing, Attention To Detail, Spotting Differences.

    Lean Analytics steers you in the right direction.This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without.Understand Lean Startup, analytics fundamentals, and the data-driven mindsetLook at six sample business models and how they map to new ventures of all sizesFind the One Metric That Matters to youLearn how to draw a line in the sand, so you’ll know it’s time to move forwardApply Lean Analytics principles to large enterprises and established products

    It should be labelled 'start here'." --Pieter Jan Stappers, ID-StudioLab, Delft University of Technology

    We are bombarded with more information each day than our brains can process—especially in election season. It's raining bad data, half-truths, and even outright lies. New York Times bestselling author Daniel J. Levitin shows how to recognize misleading announcements, statistics, graphs, and written reports revealing the ways lying weasels can use them. It's becoming harder to separate the wheat from the digital chaff. How do we distinguish misinformation, pseudo-facts, distortions, and outright lies from reliable information? Levitin groups his field guide into two categories—statistical infomation and faulty arguments—ultimately showing how science is the bedrock of critical thinking. Infoliteracy means understanding that there are hierarchies of source quality and bias that variously distort our information feeds via every media channel, including social media. We may expect newspapers, bloggers, the government, and Wikipedia to be factually and logically correct, but they so often aren't. We need to think critically about the words and numbers we encounter if we want to be successful at work, at play, and in making the most of our lives. This means checking the plausibility and reasoning—not passively accepting information, repeating it, and making decisions based on it. Readers learn to avoid the extremes of passive gullibility and cynical rejection. Levitin's charming, entertaining, accessible guide can help anyone wake up to a whole lot of things that aren't so. And catch some lying weasels in their tracks!

    “I started my PhD in September 2003, but it wasn’t long before I realised that it’s much easier to get onto a PhD programme than it is to complete one…”If the aim of a PhD is to develop the skills of a professional academic researcher, how should you go about it? Using the principles of skill development as a foundation, this book provides a unique approach to the most common challenges of PhD research, including:Getting to know the literature in your fieldDeveloping your research ideasBecoming a better academic writerCoping with the stress and unpredictability of researchPublications and presentationsWriting, submitting and defending your thesis

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    In this lively and groundbreaking new book, economist Ian Ayres shows how today's best and brightest organizations are analyzing massive databases at lightening speed to provide greater insights into human behavior. They are the Super Crunchers. From internet sites like Google and Amazon that know your tastes better than you do, to a physician's diagnosis and your child's education, to boardrooms and government agencies, this new breed of decision makers are calling the shots. And they are delivering staggeringly accurate results. How can a football coach evaluate a player without ever seeing him play? Want to know whether the price of an airline ticket will go up or down before you buy? How can a formula outpredict wine experts in determining the best vintages? Super crunchers have the answers. In this brave new world of equation versus expertise, Ayres shows us the benefits and risks, who loses and who wins, and how super crunching can be used to help, not manipulate us.Gone are the days of solely relying on intuition to make decisions. No businessperson, consumer, or student who wants to stay ahead of the curve should make another keystroke without reading Super Crunchers.

    The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors

    It is the definitive reference guide, now in a second edition. Although the first edition was written in 1978, it continues to be a worldwide best-seller. This second edition brings the classic original up to date to include the ANSI standard. From the Preface: We have tried to retain the brevity of the first edition. C is not a big language, and it is not well served by a big book. We have improved the exposition of critical features, such as pointers, that are central to C programming. We have refined the original examples, and have added new examples in several chapters. For instance, the treatment of complicated declarations is augmented by programs that convert declarations into words and vice versa. As before, all examples have been tested directly from the text, which is in machine-readable form. As we said in the first preface to the first edition, C "wears well as one's experience with it grows." With a decade more experience, we still feel that way. We hope that this book will help you to learn C and use it well.

    Bolman and Joan V. Gallos offer higher education leaders a provocative and pragmatic guide forCrafting dynamic institutions where the whole is greater than the sum of the parts Creating campus environments that facilitate creativity and commitment Forging alliances and partnerships in service of the mission Building shared vision and campus cultures that unite and inspire Serving the larger goals of the academy and society Throughout the book, the authors integrate powerful conceptual frameworks with rich and compelling real-world cases to support academic leaders searching for the best in themselves and in their institutions. The book tackles thorny issues such as building institutional clarity and capacity, managing conflict, coping with difficult people, partnering with the boss, and developing leadership resilience.Following in the tradition of Bolman and Deal's classic Reframing Organizations, Bolman and Gallos emphasize a pragmatic approach. They tease out the unique challenges and opportunities in academic leadership and provide ideas, tools, and encouragement to help higher education leaders see more clearly, feel more confident, and become more skilled and versatile in handling the vicissitudes of daily life. Reframing Academic Leadership is the resource for those seeking to understand, develop, and manage colleges and universities.

    Individual teachers, as reflective practitioners, still need to make their own decisions about how they are going to get students actively involved in large classes, to teach international students, and to assess in ways that enhance the quality of learning. But now that quality assurance and quality enhancement are required at the institutional level, the concept of constructive alignment is applied to the reflective institution, where it becomes a powerful underpinning to quality enhancement procedures. widespread than expected, leaving some teachers apprehensive about what it might mean for them. A new chapter elaborates on how ET can be used to enhance learning, but with a warning that any tool, electronic or otherwise, is as good as the thoughtful use to which it is put. interested in enhancing their teaching and their students' learning, and for administrators and teaching developers who are involved in teaching-related decisions on an institutional basis.

    This concise introduction shows you how OAuth provides a single authorization technology across numerous APIs on the Web, so you can securely access users’ data—such as user profiles, photos, videos, and contact lists—to improve their experience of your application.Through code examples, step-by-step instructions, and use-case examples, you’ll learn how to apply OAuth 2.0 to your server-side web application, client-side app, or mobile app. Find out what it takes to access social graphs, store data in a user’s online filesystem, and perform many other tasks.Understand OAuth 2.0’s role in authentication and authorizationLearn how OAuth’s Authorization Code flow helps you integrate data from different business applicationsDiscover why native mobile apps use OAuth differently than mobile web appsUse OpenID Connect and eliminate the need to build your own authentication system

    It is not a mere reorganization of the data into a new kind of library catalogue, nor another specualtive philosophy about the nature of man and language, but rather a rigorus explication of our intuitions about our language in terms of an overt axiom system, the theorems derivable from it, explicit results which may be compared with new data and other intuitions, all based plainly on an overt theory of the internal structure of languages; and it may well provide an opportunity for the application of explicity measures of simplicity to decide preference of one form over another form of grammar.

    No other job pulls people in so many directions at once. Users interrupt you constantly with requests, preventing you from getting anything done. Your managers want you to get long-term projects done but flood you with reques ... Available here:readmeaway.com/download?i=0596007833Time Management for System Administrators: Stop Working Late and Start Working Smart PDF by Thomas A. LimoncelliRead Time Management for System Administrators: Stop Working Late and Start Working Smart PDF from O'Reilly Media,Thomas A. LimoncelliDownload Thomas A. Limoncelli’s PDF E-book Time Management for System Administrators: Stop Working Late and Start Working Smart