“Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    Want to impress your coworkers and write the fastest, most efficient, stable code you ever have? Don't reinvent the wheel. Reuse decades of research into battle-tested, highly optimized, and proven techniques available on any Unix system.This book will teach you what you need to know so that you can write your own servers, debug your entire stack when things go awry, and understand how things are working under the hood.http://www.jstorimer.com/products/wor...

    At the same time, Steve Jobs was being forced out of his beloved Apple and starting over with a new company, NeXT Computer. His goal was to build a supercomputer with the power to transform education. Menuez had found his story: he proposed to photograph Jobs and his extraordinary team as they built this new computer, from conception to product launch. In an amazing act of trust, Jobs granted Menuez unlimited access to the company, and, for the next three years, Menuez was able to get on film the spirit and substance of innovation through the day-to-day actions of the world’s top technology guru. From there, the project expanded to include the most trailblazing companies in Silicon Valley, all of which granted Menuez the same complete access that Jobs had. Menuez photographed behind the scenes with John Warnock at Adobe, John Sculley at Apple, Bill Gates at Microsoft, John Doerr at Kleiner Perkins, Bill Joy at Sun Microsystems, Gordon Moore and Andy Grove at Intel, Marc Andreessen at Netscape, and more than seventy other leading companies and innovators. It would be fifteen years before Menuez stopped taking pictures, just as the dotcom bubble burst. An extraordinary era was coming to its close. With his singular behind-the-scenes access to these notoriously insular companies, Menuez was present for moments of heartbreaking failure and unexpected success, moments that made history, and moments that revealed the everyday lives of the individuals who made it happen. This period of rapid, radical change would affect almost every aspect of our culture and our lives in ways both large and small and would also create more jobs and wealth than any other time in human history. And Doug Menuez was there, a witness to a revolution. In more than a hundred photographs and accompanying commentary, Fearless Genius captures the human face of innovation and shows what it takes to transform powerful ideas into reality.

    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.

    When John Hargrave first invested in cryptocurrency, the price of a single bitcoin was about $125; a few years later, that same bitcoin was worth $20,000. He wasn’t alone: this flood of new money is like the early days of the Internet, creating a new breed of “blockchain billionaires.” Sir John has unlocked their secrets. In Blockchain for Everyone, Sir John reveals the formula for investing in bitcoin and blockchain, using real-life stories, easy-to-understand examples, and a healthy helping of humor. Packed with illustrations, Blockchain for Everyone explains how (and when) to buy bitcoin, cryptocurrencies, and other blockchain assets, with step-by-step instructions. Blockchain for Everyone is the first blockchain investing book written for the layperson: a guide that helps everyone understand how to build wealth wisely. It’s the new investing manifesto!

    This fast-moving narrative starts at ground zero, with the dramatic incubation of open-source software by Linux and its enigmatic creator, Linus Torvalds. With firsthand accounts, it describes how a motley group of programmers managed to shake up the computing universe and cause a radical shift in thinking for the post-Microsoft era. A powerful and engaging tale of innovation versus big business, Rebel Code chronicles the race to create and perfect open-source software, and provides the ideal perch from which to explore the changes that cyberculture has engendered in our society. Based on over fifty interviews with open-source protagonists such as Torvalds and open source guru Richard Stallman, Rebel Code captures the voice and the drama behind one of the most significant business trends in recent memory.

    By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes. Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.

    

    Mike Loukides kicked things off in June 2010 with “What is data science?” and from there we’ve pursued the various threads and themes that naturally emerged. Now, roughly a year later, we can look back over all we’ve covered and identify a number of core data areas: Data issues -- The opportunities and ambiguities of the data space are evident in discussions around privacy, the implications of data-centric industries, and the debate about the phrase “data science” itself. The application of data: products and processes – A “data product” can emerge from virtually any domain, including everything from data startups to established enterprises to media/journalism to education and research. Data science and data tools -- The tools and technologies that drive data science are of course essential to this space, but the varied techniques being applied are also key to understanding the big data arena.The business of data – Take a closer look at the actions connected to data -- the finding, organizing, and analyzing that provide organizations of all sizes with the information they need to compete.

    Foremost on that list is mobility, since going wireless frees you from the tether of an Ethernet cable at a desk. But that's just the tip of the cable-free iceberg. Wireless networks are also more flexible, faster and easier for you to use, and more affordable to deploy and maintain.The de facto standard for wireless networking is the 802.11 protocol, which includes Wi-Fi (the wireless standard known as 802.11b) and its faster cousin, 802.11g. With easy-to-install 802.11 network hardware available everywhere you turn, the choice seems simple, and many people dive into wireless computing with less thought and planning than they'd give to a wired network. But it's wise to be familiar with both the capabilities and risks associated with the 802.11 protocols. And 802.11 Wireless Networks: The Definitive Guide, 2nd Edition is the perfect place to start.This updated edition covers everything you'll ever need to know about wireless technology. Designed with the system administrator or serious home user in mind, it's a no-nonsense guide for setting up 802.11 on Windows and Linux. Among the wide range of topics covered are discussions on:deployment considerationsnetwork monitoring and performance tuningwireless security issueshow to use and select access pointsnetwork monitoring essentialswireless card configurationsecurity issues unique to wireless networksWith wireless technology, the advantages to its users are indeed plentiful. Companies no longer have to deal with the hassle and expense of wiring buildings, and households with several computers can avoid fights over who's online. And now, with 802.11 Wireless Networks: The Definitive Guide, 2nd Edition, you can integrate wireless technology into your current infrastructure with the utmost confidence.

    

    By “reverse engineering the fastest growing company in the history of the world,” author Jeff Jarvis, proprietor of Buzzmachine.com, one of the Web’s most widely respected media blogs, offers indispensible strategies for solving the toughest new problems facing businesses today. With a new afterword from the author, What Would Google Do? is the business book that every leader or potential leader in every industry must read.

    Banks, telecommunications companies, and critical government networks (including the British Parliament and the French and German military) were infected. No one had ever seen anything like it. By January 2009 the worm lay hidden in at least eight million computers and the botnet of linked computers that it had created was big enough that an attack might crash the world. This is the gripping tale of the group of hackers, researches, millionaire Internet entrepreneurs, and computer security experts who united to defend the Internet from the Conficker worm: the story of the first digital world war.

    From creating new data-driven products through to increasing operational efficiency, big data has the potential to makeyour organization both more competitive and more innovative.As this emerging field transitions from the bleeding edge to enterprise infrastructure, it's vital to understand not only the technologies involved, but the organizational and cultural demands of being data-driven.Written by O'Reilly Radar's experts on big data, this anthology describes:- The broad industry changes heralded by the big data era- What big data is, what it means to your business, and how to start solving data problems- The software that makes up the Hadoop big data stack, and the major enterprise vendors' Hadoop solutions- The landscape of NoSQL databases and their relative merits- How visualization plays an important part in data work

    The vision behind Clojure is of a radically simple language framework holding together a sophisticated collection of programming features. Learning Clojure involves much more than just learning the mechanics of the language. To really get Clojure you need to understand the ideas underlying this structure of framework and features. You need this book: an accessible introduction to Clojure that focuses on the ideas behind the language as well as the practical details of writing code.