Learn critical lessons from a person who helped design and build one of the largest high-performance .NET systems in the world.This book does not just teach you how the CLR works—it teaches you exactly what you need to do now to obtain the best performance today. It will expertly guide you through the nuts and bolts of extreme performance optimization in .NET, complete with in-depth examinations of CLR functionality, free tool recommendations and tutorials, useful anecdotes, and step-by-step guides to measure and improve performance.Among the topics you will learn are how to:-Choose what to measure and why-Use many amazing tools, freely available, to solve problems quickly-Understand the .NET garbage collector and its effect on your application-Use effective coding patterns that lead to optimal garbage collection performance-Diagnose common GC-related issues-Reduce costs of JITting-Use multiple threads sanely and effectively, avoiding synchronization problems-Know which .NET features and APIs to use and which to avoid-Use code generation to avoid performance problems-Measure everything and expose hidden performance issues-Instrument your program with performance counters and ETW events-Use the latest and greatest .NET features-Ensure your code can run on mobile devices without problems-Build a performance-minded team…and much more.

    In Enterprise Architecture as Strategy: Creating a Foundation for Business Execution, authors Jeanne W. Ross, Peter Weill, and David C. Robertson show you how.The key? Make tough decisions about which processes you must execute well, then implement the IT systems needed to digitize those processes. Citing numerous companies worldwide, the authors show how constructing the right enterprise architecture enhances profitability and time to market, improves strategy execution, and even lowers IT costs. Though clear, engaging explanation, they demonstrate how to define your operating model—your vision of how your firm will survive and grow—and implement it through your enterprise architecture. Their counterintuitive but vital message: when it comes to executing your strategy, your enterprise architecture may matter far more than your strategy itself.

    This is necessary because, in the words of Michael Polanyi, "we can know more than we can tell." Our design choices are not the result of an ineluctable chain of logic; they come from a deeper place, one which is visceral and inarticulate.Polanyi calls this "tacit knowledge", a thing which we only understand as part of something else. When we speak, we do not focus on making sounds, we focus on our words. We understand the muscular act of speech, but would struggle to explain it.To write software, we must learn where to draw boundaries. Good software is built through effective indirection. We seem to have decided that this skill can only be learned through practice; it cannot be taught, except by example. Our decisions may improve with time, but not our ability to explain them. It's true that the study of these questions cannot yield a closed-form solution for judging software design. We can make our software simple, but we cannot do the same to its problem domain, its users, or the physical world. Our tacit knowledge of this environment will always inform our designs.This doesn't mean that we can simply ignore our design process. Polanyi tells us that tacit knowledge only suffices until we fail, and the software industry is awash with failure. Our designs may never be provably correct, but we can give voice to the intuition that shaped them. Our process may always be visceral, but it doesn't have to be inarticulate.And so this book does not offer knowledge, it offers clarity. It is aimed at readers who know Clojure, but struggle to articulate the rationale of their designs to themselves and others. Readers who use other languages, but have a passing familiarity with Clojure, may also find this book useful.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    The RESTful approach to web services design is rapidly become the approach of choice. Unfortunately, too few people have truly solid REST API design skills, and discussions of REST can become bogged down in dry theory.The REST API Design Handbook is a simple, practical guide to aid software engineers and software architects create lasting, scalable APIs based on REST architectural principles. The book provides a sound foundation in discussing the constraints that define a REST API. It quickly goes beyond that into the practical aspects of implementing such an API in the real world.Written by cloud computing expert George Reese, The REST API Design Handbook reflects hands on work in consuming many different third party APIs as well the development of REST-based web services APIs. It addresses all of the debates the commonly arise while creating these APIs. Subjects covered include:* REST architectural constraints* Using HTTP methods and response codes in an API* Authenticating RESTful API calls* Versioning* Asynchronous Operations* Pagination and Streaming* Polling and Push Notifications* Rate Limiting

    It discusses cloud concepts and highlights various design patterns and best practices. This documentation is offered for free here as a Kindle book, or you can read it in PDF format at https://aws.amazon.com/whitepapers/.