When inexperienced entrepreneurs ask my advice about their idea for a tech startup, they often worry "What if Google decides to compete with us? They will crush us!" I respond that far more startups die of suicide than homicide. If you can avoid hurting yourself, then you are already better off than most of your competitors. Startups are a chance to build something entirely original with brilliant and ambitious people. But startups are also dangerous. Limited money means there is little room for mistakes. One bad decision can mean bankruptcy. The potential payoff attracts capital, which in turn attracts scam artists. The unscrupulous often lack the skills needed to succeed, but sometimes they are smart enough to trick investors. Even entrepreneurs who start with a strong moral compass can find that the threat of failure unmoors their ethics from their ambition. Emotions matter. We might hope that those in leadership positions possess strength and resilience, but vanity and fragile egos have sabotaged many of the businesses that I’ve worked with. Defeat is always a possibility, and not everyone finds healthy ways to deal with the stress. In this book I offer both advice and also warnings. I've seen certain self-destructive patterns play out again and again, so I wanted to document one of the most extreme cases that I've witnessed. In 2015 I worked for a startup that began with an ingenious idea: to use the software techniques known as Natural Language Processing to allow people to interact with databases by writing ordinary English sentences. This was a multi-billion dollar idea that could have transformed the way people gathered and used information. However, the venture had inexperienced leadership. They burned through their $1.3 million seed money. As their resources dwindled, their confidence transformed into doubt, which was aggravated by edicts from the Board Of Directors ordering sudden changes that effectively threw away weeks' worth of work. Every startup forces its participants into extreme positions, often regarding budget and deadlines. Often these situations are absurd to the point of parody. Therefore, there is considerable humor in this story. The collision of inexperience and desperation gives rise to moments that are simply silly. I tell this story in a day-to-day format, both to capture the early optimism, and then the later sense of panic. Here then, is a cautionary tale, a warning about tendencies that everyone joining a startup should be on guard against."

    It’s the latest in a long line of “Are you cool enough to use me?” programming languages, APIs, and toolkits. In that sense, it lands squarely in the tradition of Rails, and Ajax, and Hadoop, and even to some degree iPhone programming and HTML5.Dig a little deeper, and you’ll hear that Node.js (or, as it’s more briefly called by many, simply “Node”) is a server-side solution for JavaScript, and in particular, for receiving and responding to HTTP requests. If that doesn’t completely boggle your mind, by the time the conversation heats up with discussion of ports, sockets, and threads, you’ll tend to glaze over. Is this really JavaScript? In fact, why in the world would anyone want to run JavaScript outside of a browser, let alone the server?The good news is that you’re hearing (and thinking) about the right things. Node really is concerned with network programming and server-side request/response processing. The bad news is that like Rails, Ajax, and Hadoop before it, there’s precious little clear information available. There will be, in time — as there now is for these other “cool” frameworks that have matured — but why wait for a book or tutorial when you might be able to use Node today, and dramatically improve the maintainability.

    But not all know how to craft great code - code that is well written and easy to understand. Code Craft teaches programmers how to move beyond writing correct code to writing great code. The book covers code writing concerns, including code presentation style, variable naming, error handling, and security; and the wider issues of programming in the real world, such as good teamwork, development processes, and documentation. Code Craft presents language-agnostic advice that is relevant to all developers, from an author with loads of practical experience. A Q&A section at the end of each chapter helps readers to review the material and makes the book suited for academic use as well.

    With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective.The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.Learn how to apply the tidy text format to NLPUse sentiment analysis to mine the emotional content of textIdentify a document's most important terms with frequency measurementsExplore relationships and connections between words with the ggraph and widyr packagesConvert back and forth between R's tidy and non-tidy text formatsUse topic modeling to classify document collections into natural groupsExamine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages

    " From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required just the ability to program in a modestly extended version of C. " CUDA by Example, " written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered includeParallel programmingThread cooperationConstant memory and eventsTexture memoryGraphics interoperabilityAtomicsStreamsCUDA C on multiple GPUsAdvanced atomicsAdditional CUDA resources All the CUDA software tools you ll need are freely available for download from NVIDIA.http: //developer.nvidia.com/object/cuda-by-e...

    Focused on helping students understand and construct proofs and expanding their mathematical maturity, this best-selling text is an accessible introduction to discrete mathematics. Johnsonbaugh's algorithmic approach emphasizes problem-solving techniques. The Seventh Edition reflects user and reviewer feedback on both content and organization.