Moms in particular will welcome this trend.  A full 60% wish they had a flexible work option. But companies see advantages too in the way remote work increases their talent pool, reduces turnover, lessens their real estate footprint, and improves the ability to conduct business across multiple time zones, to name just a few advantages.  In Remote, inconoclastic authors Fried and Hansson will convince readers that letting all or part of work teams function remotely is a great idea--and they're going to show precisely how a remote work setup can be accomplished.

    With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligenceThis book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

    As the words "at work" suggest, Peter Seibel focuses on how his interviewees tackle the day–to–day work of programming, while revealing much more, like how they became great programmers, how they recognize programming talent in others, and what kinds of problems they find most interesting. Hundreds of people have suggested names of programmers to interview on the Coders at Work web site: http://www.codersatwork.com. The complete list was 284 names. Having digested everyone’s feedback, we selected 16 folks who’ve been kind enough to agree to be interviewed:- Frances Allen: Pioneer in optimizing compilers, first woman to win the Turing Award (2006) and first female IBM fellow- Joe Armstrong: Inventor of Erlang- Joshua Bloch: Author of the Java collections framework, now at Google- Bernie Cosell: One of the main software guys behind the original ARPANET IMPs and a master debugger- Douglas Crockford: JSON founder, JavaScript architect at Yahoo!- L. Peter Deutsch: Author of Ghostscript, implementer of Smalltalk-80 at Xerox PARC and Lisp 1.5 on PDP-1- Brendan Eich: Inventor of JavaScript, CTO of the Mozilla Corporation - Brad Fitzpatrick: Writer of LiveJournal, OpenID, memcached, and Perlbal - Dan Ingalls: Smalltalk implementor and designer- Simon Peyton Jones: Coinventor of Haskell and lead designer of Glasgow Haskell Compiler- Donald Knuth: Author of The Art of Computer Programming and creator of TeX- Peter Norvig: Director of Research at Google and author of the standard text on AI- Guy Steele: Coinventor of Scheme and part of the Common Lisp Gang of Five, currently working on Fortress- Ken Thompson: Inventor of UNIX- Jamie Zawinski: Author of XEmacs and early Netscape/Mozilla hackerWhat you’ll learn:How the best programmers in the world do their jobWho is this book for?Programmers interested in the point of view of leaders in the field. Programmers looking for approaches that work for some of these outstanding programmers.

     At any given moment, somewhere in the world someone struggles with the same software design problems you have. You know you don't want to reinvent the wheel (or worse, a flat tire), so you look to Design Patterns--the lessons learned by those who've faced the same problems. With Design Patterns, you get to take advantage of the best practices and experience of others, so that you can spend your time on...something else. Something more challenging. Something more complex. Something more fun. You want to learn about the patterns that matter--why to use them, when to use them, how to use them (and when NOT to use them). But you don't just want to see how patterns look in a book, you want to know how they look "in the wild". In their native environment. In other words, in real world applications. You also want to learn how patterns are used in the Java API, and how to exploit Java's built-in pattern support in your own code. You want to learn the real OO design principles and why everything your boss told you about inheritance might be wrong (and what to do instead). You want to learn how those principles will help the next time you're up a creek without a design pattern. Most importantly, you want to learn the "secret language" of Design Patterns so that you can hold your own with your co-worker (and impress cocktail party guests) when he casually mentions his stunningly clever use of Command, Facade, Proxy, and Factory in between sips of a martini. You'll easily counter with your deep understanding of why Singleton isn't as simple as it sounds, how the Factory is so often misunderstood, or on the real relationship between Decorator, Facade and Adapter. With Head First Design Patterns, you'll avoid the embarrassment of thinking Decorator is something from the "Trading Spaces" show. Best of all, in a way that won't put you to sleep! We think your time is too important (and too short) to spend it struggling with academic texts. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. Using the latest research in neurobiology, cognitive science, and learning theory, Head First Design Patterns will load patterns into your brain in a way that sticks. In a way that lets you put them to work immediately. In a way that makes you better at solving software design problems, and better at speaking the language of patterns with others on your team.

    A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones. Using vivid examples, John MacCormick explains the fundamental "tricks" behind nine types of computer algorithms, including artificial intelligence (where we learn about the "nearest neighbor trick" and "twenty questions trick"), Google's famous PageRank algorithm (which uses the "random surfer trick"), data compression, error correction, and much more. These revolutionary algorithms have changed our world: this book unlocks their secrets, and lays bare the incredible ideas that our computers use every day.

    This updated edition includes all the changes in Python 3, itself a significant shift from earlier versions of Python.The book begins with basic but useful programs that teach the core features of syntax, control flow, and data structures. It then moves to larger applications involving code management, object-oriented programming, web development, and converting code from earlier versions of Python.True to his audience of experienced developers, the author covers common programming language features concisely, while giving more detail to those features unique to Python.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.

    Rather than a "how to" for hands-on techies, the book entices lay-readers and experts alike by covering new case studies and the latest state-of-the-art techniques.You have been predicted — by companies, governments, law enforcement, hospitals, and universities. Their computers say, "I knew you were going to do that!" These institutions are seizing upon the power to predict whether you're going to click, buy, lie, or die.Why? For good reason: predicting human behavior combats financial risk, fortifies healthcare, conquers spam, toughens crime fighting, and boosts sales.How? Prediction is powered by the world's most potent, booming unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn.Predictive analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future — lifting a bit of the fog off our hazy view of tomorrow — means pay dirt.In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: -What type of mortgage risk Chase Bank predicted before the recession. -Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves. -Why early retirement decreases life expectancy and vegetarians miss fewer flights. -Five reasons why organizations predict death, including one health insurance company. -How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual. -How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! -How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. -How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free. -What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia. A truly omnipresent science, predictive analytics affects everyone, every day. Although largely unseen, it drives millions of decisions, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.Predictive analytics transcends human perception. This book's final chapter answers the riddle: What often happens to you that cannot be witnessed, and that you can't even be sure has happened afterward — but that can be predicted in advance?Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.

    Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering.Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more.Dorset House Publishing is proud to make this important text available to new generations of programmers -- and to encourage readers of the first edition to return to its valuable lessons.

    Cassandra: The Definitive Guide provides the technical details and practical examples you need to assess this database management system and put it to work in a production environment.Author Eben Hewitt demonstrates the advantages of Cassandra's nonrelational design, and pays special attention to data modeling. If you're a developer, DBA, application architect, or manager looking to solve a database scaling issue or future-proof your application, this guide shows you how to harness Cassandra's speed and flexibility.Understand the tenets of Cassandra's column-oriented structureLearn how to write, update, and read Cassandra dataDiscover how to add or remove nodes from the cluster as your application requiresExamine a working application that translates from a relational model to Cassandra's data modelUse examples for writing clients in Java, Python, and C#Use the JMX interface to monitor a cluster's usage, memory patterns, and moreTune memory settings, data storage, and caching for better performance

    Leading Scrum coach and trainer Kenny Rubin illuminates the values, principles, and practices of Scrum, and describes flexible, proven approaches that can help you implement it far more effectively. Whether you are new to Scrum or years into your use, this book will introduce, clarify, and deepen your Scrum knowledge at the team, product, and portfolio levels. Drawing from Rubin's experience helping hundreds of organizations succeed with Scrum, this book provides easy-to-digest descriptions enhanced by more than two hundred illustrations based on an entirely new visual icon language for describing Scrum's roles, artifacts, and activities. Essential Scrum will provide every team member, manager, and executive with a common understanding of Scrum, a shared vocabulary they can use in applying it, and practical knowledge for deriving maximum value from it.

    The answers aren't easy -- just incredibly successful.

    While some fear is healthy (often viewed as a conscience that tells programmers to be careful!), the author believes that byproducts of fear include tentative, grumpy, and uncommunicative programmers who are unable to absorb constructive criticism. When programming teams buy into TDD, they immediately see positive results. They eliminate the fear involved in their jobs, and are better equipped to tackle the difficult challenges that face them. TDD eliminates tentative traits, it teaches programmers to communicate, and it encourages team members to seek out criticism However, even the author admits that grumpiness must be worked out individually! In short, the premise behind TDD is that code should be continually tested and refactored. Kent Beck teaches programmers by example, so they can painlessly and dramatically increase the quality of their work.

    This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. It is based in part on the authors blog posts, lecture materials, and tutorials. The author is one of the co-developers of the Johns Hopkins Specialization in Data Science the largest data science program in the world that has enrolled more than 1.76 million people. The book is useful as a companion to introductory courses in data science or data analysis. It is also a useful reference tool for people tasked with reading and critiquing data analyses. It is based on the authors popular open-source guides available through his Github account (https://github.com/jtleek). The paper is also available through Leanpub (https://leanpub.com/datastyle), if the book is purchased on that platform you are entitled to lifetime free updates.

    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

    What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us.In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.