Conscious Robots challenges us to face up to the reality of being human: just because we're conscious doesn't mean we're not robots. So what would we do with free will if we really had it? And how does “being a robot” explain why life, as Buddha suggested, is “inherently unsatisfactory”, despite our luxurious homes, successful careers and loving families? Conscious Robots shows why we’re so convinced that we’re in charge, when we’re really just carrying out our evolved pre-programmed instructions. And reveals the inevitable future, how one day humans will take control of their conscious minds, get happy and stay happy. But it will come too late for you, Dear Reader… so no point buying the book. Unless you’re extremely rich, of course. Then you can pay for the neurochemical research yourself. “Easy to understand and persuasive” “Reminded me of Douglas Adams and Terry Pratchett”

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    The Singularity is triggered by the tremendous growth of human and computing intelligence that is an almost inevitable outcome of Moore's Law. Since the book's publication, the coming of the Singularity is now eagerly anticipated by many of the leading thinkers in Silicon Valley, from PayPal mastermind Peter Thiel to Google co-founder Larry Page. The formation of the Singularity University, and the huge popularity of the Singularity website kurzweilai.com, speak to the importance of this intellectual movement.But what about the average person? How will the Singularity affect our daily lives—our jobs, our families, and our wealth?Singularity Rising: Surviving and Thriving in a Smarter, Richer, and More Dangerous World focuses on the implications of a future society faced with an abundance of human and artificial intelligence. James D. Miller, an economics professor and popular speaker on the Singularity, reveals how natural selection has been increasing human intelligence over the past few thousand years and speculates on how intelligence enhancements will shape civilization over the next forty years.Miller considers several possible scenarios in this coming singularity:-A merger of man and machine making society fantastically wealthy and nearly immortal-Competition with billions of cheap AIs drive human wages to almost nothing while making investors rich-Businesses rethink investment decisions to take into account an expected future period of intense creative destruction-Inequality drops worldwide as technologies mitigate the cognitive cost of living in impoverished environments-Drugs designed to fight Alzheimer's disease and keep soldiers alert on battlefields have the fortunate side effect of increasing all of their users’ IQs, which, in turn, adds a percentage points to worldwide economic growthSingularity Rising offers predictions about the economic implications for a future of widely expanding intelligence and practical career and investment advice on flourishing on the way to the Singularity.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.Use graphics to describe data with one, two, or dozens of variablesDevelop conceptual models using back-of-the-envelope calculations, as well asscaling and probability argumentsMine data with computationally intensive methods such as simulation and clusteringMake your conclusions understandable through reports, dashboards, and other metrics programsUnderstand financial calculations, including the time-value of moneyUse dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situationsBecome familiar with different open source programming environments for data analysisFinally, a concise reference for understanding how to conquer piles of data.--Austin King, Senior Web Developer, MozillaAn indispensable text for aspiring data scientists.--Michael E. Driscoll, CEO/Founder, Dataspora

    The calculus is not a hard subject and I prove this through an easy to read and obvious approach spanning only 100 pages. I have written this book with the following type of student in mind; the non-traditional student returning to college after a long break, a notoriously weak student in math who just needs to get past calculus to obtain a degree, and the garage tinkerer who wishes to understand a little more about the technical subjects. This book is meant to address the many fundamental thought-blocks that keep the average 'mathaphobe' (or just an interested person who doesn't have the time to enroll in a course) from excelling in mathematics in a clear and concise manner. It is my sincerest hope that this book helps you with your needs.Show more Show less

    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.

    Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you're ready to get started.Use R's default graphics for quick exploration of dataCreate a variety of bar graphs, line graphs, and scatter plotsSummarize data distributions with histograms, density curves, box plots, and other examplesProvide annotations to help viewers interpret dataControl the overall appearance of graphicsRender data groups alongside each other for easy comparisonUse colors in plotsCreate network graphs, heat maps, and 3D scatter plotsStructure data for graphing

    KEY TOPICS: Coverage begins with an optional review of key concepts--such as properties of compound semiconductor, quantum mechanics, semiconductor statistics, carrier transport properties, optical processes, and junction theory--then progress gradually through more advanced topics. The Second Edition has been both updated and expanded to include the recent developments in the field.

    It not only offers thorough experience and knowledge-based insights to those who are already or are contemplating serving the social emotional needs of these children in the future, but also those who profess to educate future teachers, those who would venture out into classrooms charged with the teaching and many others besides. It should be required reading for politicians - especially those who shape educational policy.--Gifted and Talented InternationalLinda Silverman is an articulate, insightful, authoritative, and extremely gifted international expert in the assessment of giftedness...[She] has created a gem with Giftedness 101. The fields of psychology and education should welcome this vibrant book with open arms.Alan S. Kaufman, PhD Yale Child Study Center School of MedicineThis is a really terrific book! I'm really impressed at how much information has been packed into it, how accessible it is (without talking down to the audience), and how well the author has parsed the many key issues in the world of giftedness. Parents and mental health professionals with find this book incredibly useful. I look forward to sharing it far and wide. I think it is a book that was badly needed and will really fill a niche.Corin Goodwin CEO & Executive Director, Gifted Homeschoolers ForumThis is the most thorough history, explanation, and call to action for gifted advocates you will find.--Laughing at Chaos BlogWhat is giftedness? Is it the potential for success or is it the experience of being an outsider? This book addresses the unique psychological needs of gifted children, which are often manifested as feeling different, and examines special issues such as gifted children with learning disabilities, gender considerations, implications of socio-economic status, and more.Giftedness 101 dispels common myths about giftedness and challenges the view that eminence is the true signifier of giftedness. It offers specific guidelines to psychologists, parents, and teachers; describes comprehensive assessment of the gifted; provides support for the twice exceptional; and focuses on the complex inner world of the gifted. The book defines giftedness as a psychological reality with powerful ramifications throughout the lifespan. Giftedness 101 will be a valuable, eye-opening resource for psychologists, educators, and other professionals who work with the gifted, as well as gifted individuals and their families.Key Features: Provides a concise, accessible overview of one of the most important and challenging topics in psychology and educationExamines the concept of giftedness across the lifespanCovers both the intellectual assessment and development of gifted individuals as well as the psychological well-being issues of this populationWritten by a prominent expert in the field of the psychology of giftedness

    This idea--using computers to spy on people and groups perceived as a threat, both at home and abroad--drove ARPA to develop the internet in the 1960s, and continues to be at the heart of the modern internet we all know and use today. As Levine shows, surveillance wasn't something that suddenly appeared on the internet; it was woven into the fabric of the technology.But this isn't just a story about the NSA or other domestic programs run by the government. As the book spins forward in time, Levine examines the private surveillance business that powers tech-industry giants like Google, Facebook, and Amazon, revealing how these companies spy on their users for profit, all while doing double duty as military and intelligence contractors. Levine shows that the military and Silicon Valley are effectively inseparable: a military-digital complex that permeates everything connected to the internet, even coopting and weaponizing the antigovernment privacy movement that sprang up in the wake of Edward Snowden.With deep research, skilled storytelling, and provocative arguments, Surveillance Valley will change the way you think about the news--and the device on which you read it.

    New topics include managing and maintaining cellular devices, including tablets; configuring operating systems, including Windows 8, Android, and iOS; and enhanced, mobile-centered security and troubleshooting procedures. The All-in-One Exam Guide enables you to take the test with complete confidence. It also serves as a practical reference for IT support and technical personnel. Bonus electronic content includes: Practice exams with hundreds of accurate questions More than an hour of video training featuring Mike Meyers Performance-based simulations that prepare you for the performance-based questions on the exam A collection of Mike's favorite free PC tools Key Features include: Written with the “in the trenches” voice and clarity Mike Meyers is known for Features pre-assessment tests, exam tips, and “Try This!” sections to reinforce difficult topics Includes a coupon for 10% off of the exam fee, a $37 value

    Highlights of the book include realistic problems and examples from a wide range of application areas. New to this edition are: much sharper pedagogy; an increase in the number of examples; more thorough development of the concepts; a greater range of homework problems; a greater number and variety of worked out examples; expanded coverage of dynamics modelling and Laplace transform topics; and integration of MATLAB, including many examples that are formatted in MATLAB.

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    In this book, William Cook takes readers on a mathematical excursion, picking up the salesman's trail in the 1800s when Irish mathematician W. R. Hamilton first defined the problem, and venturing to the furthest limits of today's state-of-the-art attempts to solve it. He also explores its many important applications, from genome sequencing and designing computer processors to arranging music and hunting for planets.In Pursuit of the Traveling Salesman travels to the very threshold of our understanding about the nature of complexity, and challenges you yourself to discover the solution to this captivating mathematical problem.