“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

    This comprehensive book will guide readers through CISSP exam topics, including: Access ControlApplication Development SecurityBusiness Continuity and Disaster Recovery PlanningCryptographyInformation Security Governance and Risk Management Legal, Regulations, Investigations and ComplianceOperations SecurityPhysical (Environmental) SecuritySecurity Architecture and DesignTelecommunications and Network SecurityThis study guide will be complete with 100% coverage of the exam objectives, real world scenarios, hands-on exercises, and challenging review questions, both in the book as well via the exclusive Sybex Test Engine.

    We're going to do that by introducing you to Example.com, where you're going to start a new job as one of its SysAdmins. The first project you'll be in charge of is developing its new log management solution. We'll teach you how to:* Install and deploy LogStash.* Ship events from a LogStash Shipper to a central LogStash server.* Filter incoming events using a variety of techniques.* Output those events to a selection of useful destinations.* Use LogStash's Web interface and alternative interfaces like Kibana.* Scale out your LogStash implementation as your environment grows.* Quickly and easily extend LogStash to deliver additional functionality you might need.By the end of the book you should have a functional and effective log management solution that you can deploy into your own environment.

    A world that is as creative and complex as it is dangerous and disturbing. A world that is much closer than you think.The dark net is an underworld that stretches from popular social media sites to the most secretive corners of the encrypted web. It is a world that frequently appears in newspaper headlines, but one that is little understood, and rarely explored. The Dark Net is a revelatory examination of the internet today, and of its most innovative and dangerous subcultures: trolls and pornographers, drug dealers and hackers, political extremists and computer scientists, Bitcoin programmers and self-harmers, libertarians and vigilantes.Based on extensive first-hand experience, exclusive interviews and shocking documentary evidence, The Dark Net offers a startling glimpse of human nature under the conditions of freedom and anonymity, and shines a light on an enigmatic and ever-changing world.

    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

    100 complete coverage of all official objectives for Exams EX200 and EX300 Exam Readiness Checklist-youre ready for the exam when all objectives on the list are checked off Inside the Exam sections in every chapter highlight key exam topics covered Two-Minute Drills for quick review 100 lab questions-two full lab-based RHCSA exams and two full lab-based RHCE exams-match the format, tone, topics, and difficulty of the real exam Covers all the exam topics, including Virtual Machines and Automated Installations Fundamental Command Line Skills RHCSA-Level Security Options The Boot Process Linux Filesystem Administration Package Management User Administration RHCSA-Level System Administration RHCE Security System Services and SELinux RHCE Administration Mail Servers Samba File Sharing DNS, FTP, and Logging CD-ROM includes Complete lab-based exam preparation, featuring Two full RHCSA practice exams Two full RHCE practice exams Lab-based chapter self tests In-depth answer explanations for all labs RHCSA and RHCE Glossary PDF copy of the book for studying on the go Michael Jang, RHCE, LPIC-2, UCP, LCP, MCP, is the author of three previous bestselling editions of RHCE Red Hat Certified Engineer Linux Study Guide and several other books on Linux and professional certification.

    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

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.

    Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age.How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more.An essential introduction to the new technologies of digital currencyCovers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much moreFeatures an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slidesAlso suitable for use with the authors' Coursera online courseElectronic solutions manual (available only to professors)

    Users demand software that is well-behaved, good-looking, and easy to use. Your clients or managers demand originality and a short time to market. Your UI technology -- web applications, desktop software, even mobile devices -- may give you the tools you need, but little guidance on how to use them well.UI designers over the years have refined the art of interface design, evolving many best practices and reusable ideas. If you learn these, and understand why the best user interfaces work so well, you too can design engaging and usable interfaces with less guesswork and more confidence.Designing Interfaces captures those best practices as design patterns -- solutions to common design problems, tailored to the situation at hand. Each pattern contains practical advice that you can put to use immediately, plus a variety of examples illustrated in full color. You'll get recommendations, design alternatives, and warnings on when not to use them.Each chapter's introduction describes key design concepts that are often misunderstood, such as affordances, visual hierarchy, navigational distance, and the use of color. These give you a deeper understanding of why the patterns work, and how to apply them with more insight.A book can't design an interface for you -- no foolproof design process is given here -- but Designing Interfaces does give you concrete ideas that you can mix and recombine as you see fit. Experienced designers can use it as a sourcebook of ideas. Novice designers will find a roadmap to the world of interface and interaction design, with enough guidance to start using these patterns immediately.

    Russ Olsen has done a great job of selecting classic patterns and augmenting these with newer patterns that have special relevance for Ruby. He clearly explains each idea, making a wealth of experience available to Ruby developers for their own daily work."--Steve Metsker, Managing Consultant with Dominion Digital, Inc."This book provides a great demonstration of the key 'Gang of Four' design patterns without resorting to overly technical explanations. Written in a precise, yet almost informal style, this book covers enough ground that even those without prior exposure to design patterns will soon feel confident applying them using Ruby. Olsen has done a great job to make a book about a classically 'dry' subject into such an engaging and even occasionally humorous read."--Peter Cooper"This book renewed my interest in understanding patterns after a decade of good intentions. Russ picked the most useful patterns for Ruby and introduced them in a straightforward and logical manner, going beyond the GoF's patterns. This book has improved my use of Ruby, and encouraged me to blow off the dust covering the GoF book."--Mike Stok" Design Patterns in Ruby is a great way for programmers from statically typed objectoriented languages to learn how design patterns appear in a more dynamic, flexible language like Ruby."--Rob Sanheim, Ruby Ninja, RelevanceMost design pattern books are based on C++ and Java. But Ruby is different--and the language's unique qualities make design patterns easier to implement and use. In this book, Russ Olsen demonstrates how to combine Ruby's power and elegance with patterns, and write more sophisticated, effective software with far fewer lines of code.After reviewing the history, concepts, and goals of design patterns, Olsen offers a quick tour of the Ruby language--enough to allow any experienced software developer to immediately utilize patterns with Ruby. The book especially calls attention to Ruby features that simplify the use of patterns, including dynamic typing, code closures, and "mixins" for easier code reuse.Fourteen of the classic "Gang of Four" patterns are considered from the Ruby point of view, explaining what problems each pattern solves, discussing whether traditional implementations make sense in the Ruby environment, and introducing Ruby-specific improvements. You'll discover opportunities to implement patterns in just one or two lines of code, instead of the endlessly repeated boilerplate that conventional languages often require. Design Patterns in Ruby also identifies innovative new patterns that have emerged from the Ruby community. These include ways to create custom objects with metaprogramming, as well as the ambitious Rails-based "Convention Over Configuration" pattern, designed to help integrate entire applications and frameworks.Engaging, practical, and accessible, Design Patterns in Ruby will help you build better software while making your Ruby programming experience more rewarding.

    It is a book I recommend." --Scott Guthrie, Corporate Vice President, .NET Developer Platform, Microsoft Corporation "A must-read for a concise but thorough examination of the parallel programming features in the .NET Framework 4." --Stephen Toub, Parallel Computing Platform Program Manager, Microsoft "This wonderful book is a great reference for developers of all levels." -- Chris Burrows, C# Compiler Team, Microsoft When you have questions about how to use C# 4.0 or the .NET CLR, this highly acclaimed bestseller has precisely the answers you need. Uniquely organized around concepts and use cases, this fourth edition includes in-depth coverage of new C# topics such as parallel programming, code contracts, dynamic programming, security, and COM interoperability. You'll also find updated information on LINQ, including examples that work with both LINQ to SQL and Entity Framework. This book has all the essential details to keep you on track with C# 4.0. Get up to speed on C# language basics, including syntax, types, and variables Explore advanced topics such as unsafe code and preprocessor directives Learn C# 4.0 features such as dynamic binding, type parameter variance, and optional and named parameters Work with .NET 4's rich set of features for parallel programming, code contracts, and the code security model Learn .NET topics, including XML, collections, I/O and networking, memory management, reflection, attributes, security, and native interoperability

    They aren't conscious of all the choices they make, like how they format their source, the names they use for variables, or the kinds of loops they use. They're focused entirely on problems they're solving, solutions they're creating, and algorithms they're implementing. So they write code in the way that seems natural, that happens intuitively, and that feels good.But if you're serious about your profession, intuition isn't enough. Perl Best Practices author Damian Conway explains that rules, conventions, standards, and practices not only help programmers communicate and coordinate with one another, they also provide a reliable framework for thinking about problems, and a common language for expressing solutions. This is especially critical in Perl, because the language is designed to offer many ways to accomplish the same task, and consequently it supports many incompatible dialects.With a good dose of Aussie humor, Dr. Conway (familiar to many in the Perl community) offers 256 guidelines on the art of coding to help you write better Perl code--in fact, the best Perl code you possibly can. The guidelines cover code layout, naming conventions, choice of data and control structures, program decomposition, interface design and implementation, modularity, object orientation, error handling, testing, and debugging.They're designed to work together to produce code that is clear, robust, efficient, maintainable, and concise, but Dr. Conway doesn't pretend that this is the one true universal and unequivocal set of best practices. Instead, Perl Best Practices offers coherent and widely applicable suggestions based on real-world experience of how code is actually written, rather than on someone's ivory-tower theories on how software ought to be created.Most of all, Perl Best Practices offers guidelines that actually work, and that many developers around the world are already using. Much like Perl itself, these guidelines are about helping you to get your job done, without getting in the way.Praise for Perl Best Practices from Perl community members:"As a manager of a large Perl project, I'd ensure that every member of my team has a copy of Perl Best Practices on their desk, and use it as the basis for an in-house style guide." -- Randal Schwartz"There are no more excuses for writing bad Perl programs. All levels of Perl programmer will be more productive after reading this book." -- Peter Scott"Perl Best Practices will be the next big important book in the evolution of Perl. The ideas and practices Damian lays down will help bring Perl out from under the embarrassing heading of "scripting languages". Many of us have known Perl is a real programming language, worthy of all the tasks normally delegated to Java and C++. With Perl Best Practices, Damian shows specifically how and why, so everyone else can see, too." -- Andy Lester"Damian's done what many thought impossible: show how to build large, maintainable Perl applications, while still letting Perl be the powerful, expressive language that programmers have loved for years." -- Bill Odom"Finally, a means to bring lasting order to the process and product of real Perl development teams." -- Andrew Sundstrom"Perl Best Practices provides a valuable education in how to write robust, maintainable P

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    "The Rails(TM) 3 Way"is the only comprehensive, authoritative guide to delivering production-quality code with Rails 3. Pioneering Rails expert Obie Fernandez and a team of leading experts illuminate the entire Rails 3 API, along with the idioms, design approaches, and libraries that make developing applications with Rails so powerful. Drawing on their unsurpassed experience and track record, they address the real challenges development teams face, showing how to use Rails 3 to maximize your productivity. Using numerous detailed code examples, the author systematically covers Rails 3 key capabilities and subsystems, making this book a reference that you will turn to again and again. He presents advanced Rails programming techniques that have been proven effective in day-to-day usage on dozens of production Rails systems and offers important insights into behavior-driven development and production considerations such as scalability. Dive deep into the Rails 3 codebase and discover why Rails is designed the way it is--and how to make it do what you want it to do.This book will help youLearn what's new in Rails 3 Increase your productivity as a web application developer Realize the overall joy in programming with Rails Leverage Rails' powerful capabilities for building REST-compliant APIs Drive implementation and protect long-term maintainability using RSpec Design and manipulate your domain layer using Active Record Understand and program complex program flows using Action Controller Master sophisticated URL routing concepts Use Ajax techniques via Rails 3 support for unobtrusive JavaScript Learn to extend Rails with popular gems and plugins, and how to write your own Extend Rails with the best third-party plug-ins and write your own Integrate email services into your applications with Action Mailer Improve application responsiveness with background processing Create your own non-Active Record domain classes using Active Model Master Rails' utility classes and extensions in Active Support