Although we are unaware of it, our brains sift through and discard billions of pieces of data in order to allow us to understand the world around us. In fact, most of what we call thought is actually the unconscious discarding of information. What our consciousness rejects constitutes the most valuable part of ourselves, the "Me" that the "I" draws on for most of our actions--fluent speech, riding a bicycle, anything involving expertise. No wonder that, in this age of information, so many of us feel empty and dissatisfied. As engaging as it is insightful, this important book encourages us to rely more on what our instincts and our senses tell us so that we can better appreciate the richness of human life.

    Schacter explores instances of what we would consider memory failure—absent-mindedness, transience, blocking, misattribution, suggestibility, bias, and persistence—and suggests instead that these miscues are actually indications that memory is functioning as designed. Drawing from vivid scientific research and creative literature, as well as high-profile events in which memory has figured significantly (Bill Clinton's grand jury testimony, for instance), The Seven Sins of Memory provides a more nuanced understanding of how memory and the mind influence each other and shape our lives.

    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

    Underlying this trend is a single idea: the belief that our existence is understandable through computation, and more data is enough to help us build a better world.   In actual fact, we are lost in a sea of information, increasingly divided by fundamentalism, simplistic narratives, conspiracy theories, and post-factual politics. Meanwhile, those in power use our lack of understanding to further their own interests. Despite the accessibility of information, we’re living in a new Dark Age.   From rogue financial systems to shopping algorithms, from artificial intelligence to state secrecy, we no longer understand how our world is governed or presented to us. The media is filled with unverifiable speculation, much of it generated by anonymous software, while companies dominate their employees through surveillance and the threat of automation.   In his brilliant new work, leading artist and writer James Bridle excavates the limits of technology and how it aids our understanding of the world. Surveying the history of art, technology, and information systems, he explores the dark clouds that gather over our dreams of the digital sublime.

    This is a deeply technical book and focuses on the software engineering skills to ace your interview. The book is over 500 pages and includes 150 programming interview questions and answers, as well as other advice.The full list of topics are as follows:The Interview ProcessThis section offers an overview on questions are selected and how you will be evaluated. What happens when you get a question wrong? When should you start preparing, and how? What language should you use? All these questions and more are answered.Behind the ScenesLearn what happens behind the scenes during your interview, how decisions really get made, who you interview with, and what they ask you. Companies covered include Google, Amazon, Yahoo, Microsoft, Apple and Facebook.Special SituationsThis section explains the process for experience candidates, Program Managers, Dev Managers, Testers / SDETs, and more. Learn what your interviewers are looking for and how much code you need to know.Before the InterviewIn order to ace the interview, you first need to get an interview. This section describes what a software engineer's resume should look like and what you should be doing well before your interview.Behavioral PreparationAlthough most of a software engineering interview will be technical, behavioral questions matter too. This section covers how to prepare for behavioral questions and how to give strong, structured responses.Technical Questions (+ 5 Algorithm Approaches)This section covers how to prepare for technical questions (without wasting your time) and teaches actionable ways to solve the trickiest algorithm problems. It also teaches you what exactly "good coding" is when it comes to an interview.150 Programming Questions and AnswersThis section forms the bulk of the book. Each section opens with a discussion of the core knowledge and strategies to tackle this type of question, diving into exactly how you break down and solve it. Topics covered include• Arrays and Strings• Linked Lists• Stacks and Queues• Trees and Graphs• Bit Manipulation• Brain Teasers• Mathematics and Probability• Object-Oriented Design• Recursion and Dynamic Programming• Sorting and Searching• Scalability and Memory Limits• Testing• C and C++• Java• Databases• Threads and LocksFor the widest degree of readability, the solutions are almost entirely written with Java (with the exception of C / C++ questions). A link is provided with the book so that you can download, compile, and play with the solutions yourself.Changes from the Fourth Edition: The fifth edition includes over 200 pages of new content, bringing the book from 300 pages to over 500 pages. Major revisions were done to almost every solution, including a number of alternate solutions added. The introductory chapters were massively expanded, as were the opening of each of the chapters under Technical Questions. In addition, 24 new questions were added.Cracking the Coding Interview, Fifth Edition is the most expansive, detailed guide on how to ace your software development / programming interviews.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Gardner's trailblazing book revolutionized the worlds of education and psychology by positing that rather than a single type of intelligence, we have several--most of which are neglected by standard testing and educational methods.More than 200,00 copies of earlier editions have been sold; this reissue includes a new introduction by the author to mark the twenty-first birthday of this remarkable book.Download PDFhttp://uploading.com/files/ae6de5f6/0...http://www.filesonic.com/file/1882814...http://depositfiles.com/files/vx6nj38a9

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    In Consilience  (a word that originally meant "jumping together"), Edward O. Wilson renews the Enlightenment's search for a unified theory of knowledge in disciplines that range from physics to biology, the social sciences and the humanities.Using the natural sciences as his model, Wilson forges dramatic links between fields. He explores the chemistry of the mind and the genetic bases of culture. He postulates the biological principles underlying works of art from cave-drawings to Lolita. Presenting the latest findings in prose of wonderful clarity and oratorical eloquence, and synthesizing it into a dazzling whole, Consilience is science in the path-clearing traditions of Newton, Einstein, and Richard Feynman.

    This bold and brilliant book asks the ultimate question of the life sciences: How did the human mind acquire its incomparable power? In seeking the answer, Merlin Donald traces the evolution of human culture and cognition from primitive apes to artificial intelligence, presenting an enterprising and original theory of how the human mind evolved from its presymbolic form.

    Not in an editor, IDE, or design tool. You're well educated on how to work with software and hardware, but what about wetware--our own brains? Learning new skills and new technology is critical to your career, and it's all in your head. In this book by Andy Hunt, you'll learn how our brains are wired, and how to take advantage of your brain's architecture. You'll learn new tricks and tips to learn more, faster, and retain more of what you learn. You need a pragmatic approach to thinking and learning. You need to Refactor Your Wetware. Programmers have to learn constantly; not just the stereotypical new technologies, but also the problem domain of the application, the whims of the user community, the quirks of your teammates, the shifting sands of the industry, and the evolving characteristics of the project itself as it is built. We'll journey together through bits of cognitive and neuroscience, learning and behavioral theory. You'll see some surprising aspects of how our brains work, and how you can take advantage of the system to improve your own learning and thinking skills.In this book you'll learn how to:Use the Dreyfus Model of Skill Acquisition to become more expertLeverage the architecture of the brain to strengthen different thinking modesAvoid common "known bugs" in your mindLearn more deliberately and more effectivelyManage knowledge more efficientlyPrinted in full color.

    On the one hand, we struggle to survive on our own in the wild, often unable to solve basic problems, like obtaining food, building shelters, or avoiding predators. On the other hand, human groups have produced innovative technologies, sophisticated languages, and complex institutions that have permitted us to successfully expand into environments across the globe. What has enabled us to dominate such a vast range of environments, more than any other species? As this book shows, the secret of our success lies not in our innate intelligence, but in our collective brains--in the ability of human groups to socially interconnect and learn from one another.Drawing insights from lost European explorers, clever chimpanzees, hunter-gatherers, neuroscientists, ancient bones, and the human genome, Joseph Henrich demonstrates how our collective brains have propelled our species' genetic evolution and shaped our biology. Our early capacities for learning from others produced many innovations, such as fire, cooking, water containers, plant knowledge, and projectile weapons, which in turn drove the expansion of our brains and altered our physiology, anatomy, and psychology in crucial ways. Further on, some collective brains generated and recombined powerful concepts, such as the lever, wheel, screw, and writing. Henrich shows how our genetics and biology are inextricably interwoven with cultural evolution, and that this particular culture-gene interaction has propelled our species on an extraordinary evolutionary trajectory.Tracking clues from our ancient past to the present, "The Secret of Our Success" explores how our cultural and social natures produce a collective intelligence that explains both our species' immense success and our human uniqueness.

    Compelling evidence shows that genetics plays a more important role than environment as intelligence develops from childhood, and that intelligence test scores correspond strongly to specific features of the brain assessed with neuroimaging. In understandable language, Richard J. Haier explains cutting-edge techniques based on genetics, DNA, and imaging of brain connectivity and function. He dispels common misconceptions, such as the belief that IQ tests are biased or meaningless, and debunks simple interventions alleged to increase intelligence. Readers will learn about the real possibility of dramatically enhancing intelligence based on neuroscience findings and the positive implications this could have for education and social policy. The text also explores potential controversies surrounding neuro-poverty, neuro-socioeconomic status, and the morality of enhancing intelligence for everyone. Online resources, including additional visuals, animations, questions and links, reinforce the material.

    With this book, you'll learn how to load data, assemble and disassemble data objects, navigate R's environment system, write your own functions, and use all of R's programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You'll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer's memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R's package system and debugging toolsPractice and apply R programming concepts as you learn them

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect