Available here:readmeaway.com/download?i=1593279523The Linux Command Line, 2nd Edition: A Complete Introduction PDF by William ShottsRead The Linux Command Line, 2nd Edition: A Complete Introduction PDF from No Starch Press,William ShottsDownload William Shotts’s PDF E-book The Linux Command Line, 2nd Edition: A Complete Introduction

    Its authors present a new view of cognition that has important social and ethical implications, for, they assert, the only world we humans can have is the one we create together through the actions of our coexistence. Written for a general audience as well as for students, scholars, and scientists and abundantly illustrated with examples from biology, linguistics, and new social and cultural phenomena, this revised edition includes a new afterword by Dr. Varela, in which he discusses the effect the book has had in the years since its first publication.

    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

    The average young person in the UK will spend 10,000 hours gaming by the age of twenty-one. What's causing this mass exodus? According to world-renowned game designer Jane McGonigal the answer is simple: videogames are fulfilling genuine human needs. Drawing on positive psychology, cognitive science and sociology, Reality is Broken shows how game designers have hit on core truths about what makes us happy, and utilized these discoveries to astonishing effect in virtual environments. But why, McGonigal asks, should we use the power of games for escapist entertainment alone? In this groundbreaking exploration of the power and future of gaming, she reveals how gamers have become expert problem solvers and collaborators, and shows how we can use the lessons of game design to socially positive ends, be it in our own lives, our communities or our businesses. Written for gamers and non-gamers alike, Reality is Broken sends a clear and provocative message: the future will belong to those who can understand, design and play games.

    Readers will progress from building a basic physics engine to creating intelligent moving objects and complex systems, setting the foundation for further experiments in generative design. Subjects covered include forces, trigonometry, fractals, cellular automata, self-organization, and genetic algorithms. The book's examples are written in Processing, an open-source language and development environment built on top of the Java programming language. On the book's website (http://www.natureofcode.com), the examples run in the browser via Processing's JavaScript mode.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    In this much-anticipated book, Michael Tomasello weaves his twenty years of comparative studies of humans and great apes into a compelling argument that cooperative social interaction is the key to our cognitive uniqueness. Once our ancestors learned to put their heads together with others to pursue shared goals, humankind was on an evolutionary path all its own.Tomasello argues that our prehuman ancestors, like today's great apes, were social beings who could solve problems by thinking. But they were almost entirely competitive, aiming only at their individual goals. As ecological changes forced them into more cooperative living arrangements, early humans had to coordinate their actions and communicate their thoughts with collaborative partners. Tomasello's "shared intentionality hypothesis" captures how these more socially complex forms of life led to more conceptually complex forms of thinking. In order to survive, humans had to learn to see the world from multiple social perspectives, to draw socially recursive inferences, and to monitor their own thinking via the normative standards of the group. Even language and culture arose from the preexisting need to work together. What differentiates us most from other great apes, Tomasello proposes, are the new forms of thinking engendered by our new forms of collaborative and communicative interaction.A Natural History of Human Thinking is the most detailed scientific analysis to date of the connection between human sociality and cognition.

    It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Yet for all the talk about the democratizing power of the Internet, regimes in Iran and China are as stable and repressive as ever. In fact, authoritarian governments are effectively using the Internet to suppress free speech, hone their surveillance techniques, disseminate cutting-edge propaganda, and pacify their populations with digital entertainment. Could the recent Western obsession with promoting democracy by digital means backfire?In this spirited book, journalist and social commentator Evgeny Morozov shows that by falling for the supposedly democratizing nature of the Internet, Western do-gooders may have missed how it also entrenches dictators, threatens dissidents, and makes it harder - not easier - to promote democracy. Buzzwords like "21st-century statecraft" sound good in PowerPoint presentations, but the reality is that "digital diplomacy" requires just as much oversight and consideration as any other kind of diplomacy.Marshaling compelling evidence, Morozov shows why we must stop thinking of the Internet and social media as inherently liberating and why ambitious and seemingly noble initiatives like the promotion of "Internet freedom" might have disastrous implications for the future of democracy as a whole.

    As a student and young researcher in the 1980s, Gelernter hoped to build a program with a dial marked "focus." At maximum "focus," the program would "think" rationally, formally, reasonably. As the dial was turned down and "focus" diminished, its "mind" would start to wander, and as you dialed even lower, this artificial mind would start to free-associate, eventually ignoring the user completely as it cruised off into the mental adventures we know as sleep.While the program was a only a partial success, it laid the foundation for The Tides of Mind, a groundbreaking new exploration of the human psyche that shows us how the very purpose of the mind changes throughout the day. Indeed, as Gelernter explains, when we are at our most alert, when reasoning and creating new memories is our main mental business, the mind is a computer-like machine that keeps emotion on a short leash and attention on our surroundings. As we gradually tire, however, and descend the "mental spectrum," reasoning comes unglued. Memory ranges more freely, the mind wanders, and daydreams grow more insistent. Self-awareness fades, reflection blinks out, and at last we are completely immersed in our own minds.With far-reaching implications, Gelernter’s landmark "Spectrum of Consciousness" finally helps decode some of the most mysterious wonders of the human mind, such as the numinous light of early childhood, why dreams are so often predictive, and why sadism and masochism underpin some of our greatest artistic achievements. It’s a theory that also challenges the very notion of the mind as a machine—and not through empirical studies or "hard science" but by listening to our great poets and novelists, who have proven themselves as humanity's most trusted guides to the subjective mind and inner self.In the great introspective tradition of Wilhelm Wundt and René Descartes, David Gelernter promises to not only revolutionize our understanding of what it means to be human but also to help answer many of our most fundamental questions about the origins of creativity, thought, and consciousness.

    Negroponte's fans will want to get a copy of Being Digital, which is an edited version of the 18 articles he wrote for Wired about "being digital." Negroponte's text is mostly a history of media technology rather than a set of predictions for future technologies. In the beginning, he describes the evolution of CD-ROMs, multimedia, hypermedia, HDTV (high-definition television), and more. The section on interfaces is informative, offering an up-to-date history on visual interfaces, graphics, virtual reality (VR), holograms, teleconferencing hardware, the mouse and touch-sensitive interfaces, and speech recognition. In the last chapter and the epilogue, Negroponte offers visionary insight on what "being digital" means for our future. Negroponte praises computers for their educational value but recognizes certain dangers of technological advances, such as increased software and data piracy and huge shifts in our job market that will require workers to transfer their skills to the digital medium. Overall, Being Digital provides an informative history of the rise of technology and some interesting predictions for its future.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    His fascinating quest draws on the history of philosophy, but also anthropology, sociology, psychology and neurology; he talks to theologians, priests, allegedly reincarnated Lamas, and delves into real-life cases of lost memory, personality disorders and personal transformation; and, candidly and engagingly, he describes his own experiences. After reading "The Ego Trick," you will never see yourself in the same way again.

    These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.