It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    This book explains the technical aspects of hacking, including stack based overflows, heap based overflows, string exploits, return-into-libc, shellcode, and cryptographic attacks on 802.11b.

    “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

    Get an insider's tour of databases and client-server systems so you can understand the local customs. Then work your way up to sophisticated commands and statements, and check out the coverage of SQL-related products, such as Microsoft SQL server. You'll be able to communicate with your database like a native speaker in no time! Inside, find helpful advice on how to Get a complete overview of SQL components, such as Data Definition Language, Data Manipulation Language, and Data Control Language Use SQL to transfer and retrieve information on the Internet and intranets Uncover fundamental SQL commands and data types Extract data from many different data sources by using ODBC Master the basics of creating tables, views, schemas, and indexes for easy data access Manage databases by using SQL server Access a database over the Internet Get tips for making advanced queries

    It's the expertise you need when your start-up gets an unexpected spike in web traffic, or when a new feature causes your mature application to fail. In this collection of essays and interviews, web veterans such as Theo Schlossnagle, Baron Schwartz, and Alistair Croll offer insights into this evolving field. You'll learn stories from the trenches--from builders of some of the biggest sites on the Web--on what's necessary to help a site thrive.Learn the skills needed in web operations, and why they're gained through experience rather than schoolingUnderstand why it's important to gather metrics from both your application and infrastructureConsider common approaches to database architectures and the pitfalls that come with increasing scaleLearn how to handle the human side of outages and degradationsFind out how one company avoided disaster after a huge traffic delugeDiscover what went wrong after a problem occurs, and how to prevent it from happening againContributors include:John AllspawHeather ChampMichael ChristianRichard CookAlistair CrollPatrick DeboisEric FlorenzanoPaul HammondJustin HuffAdam JacobJacob LoomisMatt MassieBrian MoonAnoop NagwaniSean PowerEric RiesTheo SchlossnagleBaron SchwartzAndrew Shafer

    How's that possible? Google revealed the secret through a project called Kubernetes, an open source cluster orchestrator (based on its internal Borg system) that radically simplifies the task of building, deploying, and maintaining scalable distributed systems in the cloud. This practical guide shows you how Kubernetes and container technology can help you achieve new levels of velocity, agility, reliability, and efficiency.Authors Kelsey Hightower, Brendan Burns, and Joe Beda--who've worked on Kubernetes at Google--explain how this system fits into the lifecycle of a distributed application. You will learn how to use tools and APIs to automate scalable distributed systems, whether it is for online services, machine-learning applications, or a cluster of Raspberry Pi computers.Explore the distributed system challenges that Kubernetes addressesDive into containerized application development, using containers such as DockerCreate and run containers on Kubernetes, using Docker's Image format and container runtimeExplore specialized objects essential for running applications in productionReliably roll out new software versions without downtime or errorsGet examples of how to develop and deploy real-world applications in Kubernetes

    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

    When working hand-in-hand, they serve as the standard for the rapid development of dynamic, database-driven websites. This combination is so popular, in fact, that it's attracting manyprogramming newbies who come from a web or graphic design background and whose first language is HTML. If you fall into this ever-expanding category, then this book is for you."Learning PHP and MySQL" starts with the very basics of the PHP language, including strings and arrays, pattern matching and a detailed discussion of the variances in different PHP versions. Next, it explains how to work with MySQL, covering information on SQL data access for language and data fundamentals like tables and statements.Finally, after it's sure that you've mastered these separate concepts, the book shows you how to put them together to generate dynamic content. In the process, you'll also learn about error handling, security, HTTP authentication, and more.If you're a hobbyist who is intimidated by thick, complex computer books, then this guide definitely belongs on your shelf. "Learning PHP and MySQL" explains everything--from basic concepts to the nuts and bolts of performing specific tasks--in plain English.Part of O'Reilly's bestselling Learning series, the book is an easy-to-use resource designed specifically for newcomers. It's also a launching pad for future learning, providing you with a solid foundation for more advanced development.

    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.

    Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural characteristics as it evolves. This practical guide ties those parts together with a new way to think about architecture and time.

    We'll introduce you to various tips, tricks, patterns, code snippets, and techniques that we've picked up over the years.This book is great for:Beginners who have just finished the Django tutorial.Developers with intermediate knowledge of Django who want to improve their Django projects.

    The problem is that all of those lines of JavaScript code can slow down your apps. This book reveals techniques and strategies to help you eliminate performance bottlenecks during development. You'll learn how to improve execution time, downloading, interaction with the DOM, page life cycle, and more. Yahoo! frontend engineer Nicholas C. Zakas and five other JavaScript experts -- Ross Harmes, Julien Lecomte, Steven Levithan, Stoyan Stefanov, and Matt Sweeney -- demonstrate optimal ways to load code onto a page, and offer programming tips to help your JavaScript run as efficiently and quickly as possible. You'll learn the best practices to build and deploy your files to a production environment, and tools that can help you find problems once your site goes live. Identify problem code and use faster alternatives to accomplish the same task Improve scripts by learning how JavaScript stores and accesses data Implement JavaScript code so that it doesn't slow down interaction with the DOM Use optimization techniques to improve runtime performance Learn ways to ensure the UI is responsive at all times Achieve faster client-server communication Use a build system to minify files, and HTTP compression to deliver them to the browser

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Through four years of groundbreaking research, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance—and what drives it—using rigorous statistical methods. This book presents both the findings and the science behind that research. Readers will discover how to measure the performance of their teams, and what capabilities they should invest in to drive higher performance.

     -Byte, September 1995 I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up. -Charles Long If you think you're a really good programmer... read [Knuth's] Art of Computer Programming... You should definitely send me a resume if you can read the whole thing. -Bill Gates It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers. -Jonathan Laventhol This first volume in the series begins with basic programming concepts and techniques, then focuses more particularly on information structures-the representation of information inside a computer, the structural relationships between data elements and how to deal with them efficiently. Elementary applications are given to simulation, numerical methods, symbolic computing, software and system design. Dozens of simple and important algorithms and techniques have been added to those of the previous edition. The section on mathematical preliminaries has been extensively revised to match present trends in research. Ebook (PDF version) produced by Mathematical Sciences Publishers (MSP), http: //msp.org