Book picks similar to
Semi-Supervised Learning by Olivier Chapelle
machine-learning
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Untangling the Web: What the Internet is Doing to you
Aleks Krotoski - 2012
In the last decade, it has utterly transformed our lives. But what real effects is it having on our social world?What does it mean to be a modern family when dinner table conversations take place over smartphones? What happens to privacy when we readily share our personal lives with friends and corporations? Are our Facebook updates and Twitterings inspiring revolution or are they just a symptom of our global narcissism? What counts as celebrity, when everyone can have a following or be a paparazzo? And what happens to relationships when love, sex and hate can be mediated by a computer?Social psychologist Aleks Krotoski has spent a decade untangling the effects of the Web on how we work, live and play. In this groundbreaking book, she uncovers how much humanity has - and hasn't - changed because of our increasingly co-dependent relationship with the computer. In Untangling the Web, she tells the story of how the network became woven in our lives, and what it means to be alive in the age of the Internet.
Debugging: The 9 Indispensable Rules for Finding Even the Most Elusive Software and Hardware Problems
David J. Agans - 2002
Written in a frank but engaging style, Debuggingprovides simple, foolproof principles guaranteed to help find any bug quickly. This book makes those shelves of application-specific debugging books (on C++, Perl, Java, etc.) obsolete. It changes the way readers think about debugging, making those pesky problems suddenly much easier to find and fix. Illustrating the rules with real-life bug-detection war stories, the book shows readers how to: * Understand the system: how perceiving the ""roadmap"" can hasten your journey * Quit thinking and look: when hands-on investigation can’t be avoided * Isolate critical factors: why changing one element at a time can be an essential tool * Keep an audit trail: how keeping a record of the debugging process can win the day
Core Java 2, Volume I--Fundamentals (Core Series)
Cay S. Horstmann - 1999
A no-nonsense tutorial and reliable reference, this book features thoroughly tested real-world examples. The most important language and library features are demonstrated with deliberately simple sample programs, but they aren't fake and they don't cut corners. More importantly, all of the programs have been updated for J2SE 5.0 and should make good starting points for your own code. You won't find any toy examples here. This is a book for programmers who want to write real code to solve real problems. Cay S. Horstmann is a professor of computer science at San Jose State University. Previously he was vice president and chief technology officer of Preview Systems Inc. and a consultant on C++, Java, and Internet programming for major corporations, universities, and organizations. Gary Cornell has written or cowritten more than twenty popular computer books. He has a Ph.D. from Brown University and has been a visiting scientist at IBM Watson Laboratories, as well as a professor at the University of Connecticut.
Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions
Michael G. Milton - 2009
If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to:Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it useful Communicate the results of your analysis to your audience Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Data Analysis uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.
Artificial Intelligence: The Basics
Kevin Warwick - 2011
The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include:how intelligence can be defined whether machines can 'think' sensory input in machine systems the nature of consciousness the controversial culturing of human neurons.Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.
The Future Computed: Artificial Intelligence and its Role in Society
Microsoft Corporation - 2018
It’s already happening in impressive ways. But as we’ve witnessed over the past 20 years, new technology also inevitably raises complex questions and broad societal concerns.” – Brad Smith and Harry Shum on The Future Computed. “As we look to a future powered by a partnership between computers and humans, it’s important that we address these challenges head on. How do we ensure that AI is designed and used responsibly? How do we establish ethical principles to protect people? How should we govern its use? And how will AI impact employment and jobs?” – Brad Smith and Harry Shum on The Future Computed. As Artificial Intelligence shows up in every aspect of our lives, Microsoft's top minds provide a guide discussing how we should prepare for the future. Whether you're a government leader crafting new laws, an entrepreneur looking to incorporate AI into your business, or a parent contemplating the future of education, this book explains the trends driving the AI revolution, identifies the complex ethics and workforce issues we all need to think about and suggests a path forward. Read more: The Future Computed: Artificial Intelligence and its role in society provides Microsoft’s perspective on where AI technology is going and the new societal issues it is raising – ensuring AI is designed and used responsibly, establishing ethical principles to protect people, and how AI will impact employment and jobs. The principles of fairness, reliability and safety, privacy and security, inclusiveness, transparency and accountability are critical to addressing the societal impacts of AI and building trust as AI becomes more and more a part of the products and services that people use at work and at home every day. A central theme in The Future Computed is that for AI to deliver on its potential drive widespread economic and social progress, the technology needs to be human-centered – combining the capabilities of computers with human capabilities to enable people to achieve more. But a human-centered approach can only be realized if researchers, policymakers, and leaders from government, business and civil society come together to develop a shared ethical framework for AI. This in turn will help foster responsible development of AI systems that will engender trust. Because in an increasingly AI-driven world the question is not what computers can do, it is what computers should do. The Future Computed also draws a few conclusions as we chart our path forward. First, the companies and countries that will fare best in the AI era will be those that embrace these changes rapidly and effectively. Second, while AI will help solve big societal problems, we must look to this future with a critical eye as there will be challenges as well as opportunities. Third, we need to act with a sense of shared responsibility because AI won’t be created by the tech sector alone. Finally, skilling-up for an AI-powered world involves more than science, technology, engineering and math. As computers behave more like humans, the social sciences and humanities will become grow in importance.
R in a Nutshell: A Desktop Quick Reference
Joseph Adler - 2009
R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems.Understand the basics of the language, including the nature of R objectsLearn how to write R functions and build your own packagesWork with data through visualization, statistical analysis, and other methodsExplore the wealth of packages contributed by the R communityBecome familiar with the lattice graphics package for high-level data visualizationLearn about bioinformatics packages provided by Bioconductor"I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."
Wireshark 101: Essential Skills for Network Analysis
Laura A. Chappell - 2013
This book provides an ideal starting point whether you are interested in analyzing traffic to learn how an application works, you need to troubleshoot slow network performance, or determine whether a machine is infected with malware. Learning to capture and analyze communications with Wireshark will help you really understand how TCP/IP networks function. As the most popular network analyzer tool in the world, the time you spend honing your skills with Wireshark will pay off when you read technical specs, marketing materials, security briefings, and more. This book can also be used by current analysts who need to practice the skills contained in this book. In essence, this book is for anyone who really wants to know what's happening on their network.
Hadoop: The Definitive Guide
Tom White - 2009
Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!
Introductory Statistics with R
Peter Dalgaard - 2002
It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.
High Performance MySQL: Optimization, Backups, Replication & Load Balancing
Jeremy D. Zawodny - 2004
This book is an insider's guide to these little understood topics.Author Jeremy Zawodny has managed large numbers of MySQL servers for mission-critical work at Yahoo!, maintained years of contacts with the MySQL AB team, and presents regularly at conferences. Jeremy and Derek have spent months experimenting, interviewing major users of MySQL, talking to MySQL AB, benchmarking, and writing some of their own tools in order to produce the information in this book.In "High Performance MySQL" you will learn about MySQL indexing and optimization in depth so you can make better use of these key features. You will learn practical replication, backup, and load-balancing strategies with information that goes beyond available tools to discuss their effects in real-life environments. And you'll learn the supporting techniques you need to carry out these tasks, including advanced configuration, benchmarking, and investigating logs.Topics include: A review of configuration and setup optionsStorage engines and table typesBenchmarkingIndexesQuery OptimizationApplication DesignServer PerformanceReplicationLoad-balancingBackup and RecoverySecurity
Hitting Against the Spin: How Cricket Really Works
Nathan Leamon - 2021
. . lifts the curtain to reveal the inner workings of international cricket. A must-read for any cricketer, coach or fan' Eoin Morgan'This path-breaking book should be compulsory reading for commentators and captains - and all cricket fans' Mervyn King'Clever and original but also wise' Ed SmithHow valuable is winning the toss? And how should captains use it to their advantage? Why does a cricket ball swing? Why don't Indians bat left-handed? What is a good length and why? Why are leg-spinners so successful in T20 cricket? Why did England win the World Cup? Why do all Test bowlers bowl at either 55 or 85mph? Why don't they pitch it up?All cricketers long to know the answer to these questions and many more. Only fifteen years ago it would have been difficult to answer them - cricket was guided only by decades-old tradition and received wisdom. Data has changed everything. Today we can track every ball to within millimetres; its release point, speed and bounce point are measured as are how much the ball swings, how much it deviates off the pitch, the exact height and line that it passes the stumps, and multiple other variables. Hitting Against the Spin is the story of that data, and what it can tell us about how cricket really works. Leading cricket thinkers Nathan Leamon and Ben Jones lift the lid on international cricket and explain its hidden workings and dynamics - the forces that shape cricket and, in turn, the cricketers who play it. They analyse the unseen hands that determine which players succeed and which fail, which tactics work and which don't, which teams win and which lose. They also explore the new world of franchise cricket as well as the rapid evolution of the T20 format. Revolutionary in its insights, Hitting Against the Spin takes you on a fascinating whistle-stop tour of modern cricket and sports analytics, bringing cricket firmly into the twenty-first century by revealing its long-kept secrets. This is the most important cricket book in decades.
Algorithms of the Intelligent Web
Haralambos Marmanis - 2009
They use powerful techniques to process information intelligently and offer features based on patterns and relationships in data. Algorithms of the Intelligent Web shows readers how to use the same techniques employed by household names like Google Ad Sense, Netflix, and Amazon to transform raw data into actionable information.Algorithms of the Intelligent Web is an example-driven blueprint for creating applications that collect, analyze, and act on the massive quantities of data users leave in their wake as they use the web. Readers learn to build Netflix-style recommendation engines, and how to apply the same techniques to social-networking sites. See how click-trace analysis can result in smarter ad rotations. All the examples are designed both to be reused and to illustrate a general technique- an algorithm-that applies to a broad range of scenarios.As they work through the book's many examples, readers learn about recommendation systems, search and ranking, automatic grouping of similar objects, classification of objects, forecasting models, and autonomous agents. They also become familiar with a large number of open-source libraries and SDKs, and freely available APIs from the hottest sites on the internet, such as Facebook, Google, eBay, and Yahoo.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
Head First Java
Kathy Sierra - 2005
You might think the problem is your brain. It seems to have a mind of its own, a mind that doesn't always want to take in the dry, technical stuff you're forced to study. The fact is your brain craves novelty. It's constantly searching, scanning, waiting for something unusual to happen. After all, that's the way it was built to help you stay alive. It takes all the routine, ordinary, dull stuff and filters it to the background so it won't interfere with your brain's real work--recording things that matter. How does your brain know what matters? It's like the creators of the Head First approach say, suppose you're out for a hike and a tiger jumps in front of you, what happens in your brain? Neurons fire. Emotions crank up. Chemicals surge. That's how your brain knows.And that's how your brain will learn Java. Head First Java combines puzzles, strong visuals, mysteries, and soul-searching interviews with famous Java objects to engage you in many different ways. It's fast, it's fun, and it's effective. And, despite its playful appearance, Head First Java is serious stuff: a complete introduction to object-oriented programming and Java. You'll learn everything from the fundamentals to advanced topics, including threads, network sockets, and distributed programming with RMI. And the new. second edition focuses on Java 5.0, the latest version of the Java language and development platform. Because Java 5.0 is a major update to the platform, with deep, code-level changes, even more careful study and implementation is required. So learning the Head First way is more important than ever. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. You'll see why people say it's unlike any other Java book you've ever read.By exploiting how your brain works, Head First Java compresses the time it takes to learn and retain--complex information. Its unique approach not only shows you what you need to know about Java syntax, it teaches you to think like a Java programmer. If you want to be bored, buy some other book. But if you want to understand Java, this book's for you.
Python Cookbook
David Beazley - 2002
Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.Topics include:Data Structures and AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions