The book covers lambdas, streams, and functional-style programming. With Java 8's functional features you can now write more concise code in less time, and also automatically benefit from multicore architectures. It's time to dig in!

    With this hands-on guide, you'll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python's core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work"

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    Distinct from the details of implementation, algorithm, and data representation, an architecture holds the key to achieving system quality, is a reusable asset that can be applied to subsequent systems, and is crucial to a software organization's business strategy.Drawing on their own extensive experience, the authors cover the essential technical topics for designing, specifying, and validating a system. They also emphasize the importance of the business context in which large systems are designed. Their aim is to present software architecture in a real-world setting, reflecting both the opportunities and constraints that companies encounter. To that end, case studies that describe successful architectures illustrate key points of both technical and organizational discussions.Topics new to this edition include: Architecture design and analysis, including the Architecture Tradeoff Analysis Method (ATAM) Capturing quality requirements and achieving them through quality scenarios and tactics Using architecture reconstruction to recover undocumented architectures Documenting architectures using the Unified Modeling Language (UML) New case studies, including Web-based examples and a wireless Enterprise JavaBeans™ (EJB) system designed to support wearable computers The financial aspects of architectures, including use of the Cost Benefit Analysis Method (CBAM) to make decisions If you design, develop, or manage the building of large software systems (or plan to do so), or if you are interested in acquiring such systems for your corporation or government agency, use Software Architecture in Practice, Second Edition, to get up to speed on the current state of software architecture.

    Built for your brain, this book covers C# 3.0 and Visual Studio 2008, and teaches everything from language fundamentals to advanced topics including garbage collection, extension methods, and double-buffered animation. You'll also master C#'s hottest and newest syntax, LINQ, for querying SQL databases, .NET collections, and XML documents. By the time you're through, you'll be a proficient C# programmer, designing and coding large-scale applications. Every few chapters you will come across a lab that lets you apply what you've learned up to that point. Each lab is designed to simulate a professional programming task, increasing in complexity until-at last-you build a working Invaders game, complete with shooting ships, aliens descending while firing, and an animated death sequence for unlucky starfighters. This remarkably engaging book will have you going from zero to 60 with C# in no time flat.

    The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation.

    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.

    The result is a tremendous amount of time and money wasted due to wrong assumptions, lack of focus, poor communication of objectives, lack of understanding and misalignment with overall goals. There has to be a better way to deliver!This handbook is a practical guide to impact mapping, a simple yet incredibly effective method for collaborative strategic planning that helps organisations make an impact with software. Impact mapping helps to create better plans and roadmaps that ensure alignment of business and delivery, and are easily adaptable to change. Impact mapping fits nicely into several current trends in software product management and release planning, including goal-oriented requirements engineering, frequent iterative delivery, agile and lean software methods, lean startup product development cycles, and design thinking.Who is this book for?The primary audience of this book are senior people involved in building software products or delivering software projects, from both business and delivery sides. This includes business sponsors and those whose responsibilities include product ownership, project oversight or portfolio management, architecture, business analysis, quality improvement and assurance and delivery. - Business people assigned to software projects will learn how to communicate their ideas better.- Senior product or project sponsors will learn how to communicate their assumptions more effectively to delivery teams, how to engage delivery teams to make better strategic decisions, and how to manage their project portfolio more effectively.- Delivery teams that are already working under the umbrella of agile or lean delivery methods, and more recently lean startup ideas, will learn how to better focus deliverables and engage business sponsors and users.- Delivery teams moving to agile or lean delivery methods will get ideas on how to address some common issues with scaling these practices, such as creating a big picture view, splitting work into small chunks that still have business value and reporting progress more meaningfully.About the authorGojko Adzic is a strategic software delivery consultant who works with ambitious teams to improve the quality of their software products and processes. Gojko won the 2012 Jolt Award for the best book, was voted by peers as the most influential agile testing professional in 2011, and his blog won the UK Agile Award for the best online publication in 2010. To get in touch, write to gojko@neuri.co.uk or visit http://gojko.net.

    With this book, you'll get a candid and insightful look at how software is constructed and maintained by some of the world's leading practitioners.Titus Winters, Tom Manshreck, and Hyrum K. Wright, software engineers and a technical writer at Google, reframe how software engineering is practiced and taught: from an emphasis on programming to an emphasis on software engineering, which roughly translates to programming over time.You'll learn:Fundamental differences between software engineering and programmingHow an organization effectively manages a living codebase and efficiently responds to inevitable changeWhy culture (and recognizing it) is important, and how processes, practices, and tools come into play

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques that allow programmers to develop their own functional data structures. The author includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs are easily adaptable to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

    Who are these people, what motivates them, and why should you care?Consider these facts: Everything around us is turning into computers. Your typewriter is gone, replaced by a computer. Your phone has turned into a computer. So has your camera. Soon your TV will. Your car was not only designed on computers, but has more processing power in it than a room-sized mainframe did in 1970. Letters, encyclopedias, newspapers, and even your local store are being replaced by the Internet.Hackers & Painters: Big Ideas from the Computer Age, by Paul Graham, explains this world and the motivations of the people who occupy it. In clear, thoughtful prose that draws on illuminating historical examples, Graham takes readers on an unflinching exploration into what he calls “an intellectual Wild West.”The ideas discussed in this book will have a powerful and lasting impact on how we think, how we work, how we develop technology, and how we live. Topics include the importance of beauty in software design, how to make wealth, heresy and free speech, the programming language renaissance, the open-source movement, digital design, internet startups, and more.

    Over the past five years, authors Dustin Boswell and Trevor Foucher have analyzed hundreds of examples of "bad code" (much of it their own) to determine why they’re bad and how they could be improved. Their conclusion? You need to write code that minimizes the time it would take someone else to understand it—even if that someone else is you.This book focuses on basic principles and practical techniques you can apply every time you write code. Using easy-to-digest code examples from different languages, each chapter dives into a different aspect of coding, and demonstrates how you can make your code easy to understand.Simplify naming, commenting, and formatting with tips that apply to every line of codeRefine your program’s loops, logic, and variables to reduce complexity and confusionAttack problems at the function level, such as reorganizing blocks of code to do one task at a timeWrite effective test code that is thorough and concise—as well as readable"Being aware of how the code you create affects those who look at it later is an important part of developing software. The authors did a great job in taking you through the different aspects of this challenge, explaining the details with instructive examples." —Michael Hunger, passionate Software Developer

    As expected, .NET 4 brings a wealth of new APIs to the base class libraries and several new syntactical constructs to C#. For example, it is now possible to create C# methods that support optional and named arguments. As well, you are able to resolve types completely at runtime using the new dynamic keyword. As far as APIs are concerned, this edition of Pro C# 2010 and the .NET 4 Platform will cover a number of new details, including:• the Dynamic Language Runtime (DLR)• the Task Parallel Library (TPL, including PLINQ)• the ADO.NET Entity Framework (as well as LINQ to EF)• expanded coverage of the Windows Presentation Foundation (WPF) API• improved support for COM interopIf you're checking out this book for the first time, understand that it targets experienced software professionals and students of computer science—so please don't expect three chapters devoted to "variable scope" here! The mission of this text is to provide you with a rock-solid foundation in the C# programming language (including a full discussion of OOP) and the critical aspects of the .NET 4 platform.Once you digest the information presented in the book you hold in your hands, you'll be in a perfect position to apply this knowledge to your specific programming assignments, and you'll be well-equipped to explore the .NET universe on your own terms.Andrew TroelsenMicrosoft MVP, Visual Developer—Visual C#; Microsoft Certified Trainer (MCT)