More importantly, this book provides a framework for thinking about computer organization and design that will enable the reader to continue the lifetime of learning necessary for staying at the forefront of this competitive discipline. --John Crawford Intel Fellow Director of Microprocessor Architecture, Intel The performance of software systems is dramatically affected by how well software designers understand the basic hardware technologies at work in a system. Similarly, hardware designers must understand the far reaching effects their design decisions have on software applications. For readers in either category, this classic introduction to the field provides a deep look into the computer. It demonstrates the relationship between the software and hardware and focuses on the foundational concepts that are the basis for current computer design. Using a distinctive learning by evolution approach the authors present each idea from its first principles, guiding readers through a series of worked examples that incrementally add more complex instructions until they ha

    And it’s still short, profusely illustrated…and best of all–fun to read.If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Git tasks displayed on two-page spreads provide all the context you need, without the extra fluff. Get up to speed on Git right now with Pragmatic Guide to Git. Task-oriented two-page spreads get you up and running with minimal fuss. Each left-hand page dives into the underlying implementation for each task. The right-hand page contains commands that focus on the task at hand, and cross references to other tasks that are related. You'll find what you need fast. Git is rapidly becoming the de-facto standard for the open source community. Its excellent merging capabilities, coupled with its speed and relative ease of use, make it an indispensable tool for any developer. New Git users will learn the basic tasks needed to work with Git every day, including working with remote repositories, dealing with branches and tags, exploring the history, and fixing problems when things go wrong. If you're already familiar with Git, this book will be your go-to reference for Git commands and best practices. You won't find a more practical approach to learning Git than Pragmatic Guide to Git.

    "The Rails(TM) 3 Way"is the only comprehensive, authoritative guide to delivering production-quality code with Rails 3. Pioneering Rails expert Obie Fernandez and a team of leading experts illuminate the entire Rails 3 API, along with the idioms, design approaches, and libraries that make developing applications with Rails so powerful. Drawing on their unsurpassed experience and track record, they address the real challenges development teams face, showing how to use Rails 3 to maximize your productivity. Using numerous detailed code examples, the author systematically covers Rails 3 key capabilities and subsystems, making this book a reference that you will turn to again and again. He presents advanced Rails programming techniques that have been proven effective in day-to-day usage on dozens of production Rails systems and offers important insights into behavior-driven development and production considerations such as scalability. Dive deep into the Rails 3 codebase and discover why Rails is designed the way it is--and how to make it do what you want it to do.This book will help youLearn what's new in Rails 3 Increase your productivity as a web application developer Realize the overall joy in programming with Rails Leverage Rails' powerful capabilities for building REST-compliant APIs Drive implementation and protect long-term maintainability using RSpec Design and manipulate your domain layer using Active Record Understand and program complex program flows using Action Controller Master sophisticated URL routing concepts Use Ajax techniques via Rails 3 support for unobtrusive JavaScript Learn to extend Rails with popular gems and plugins, and how to write your own Extend Rails with the best third-party plug-ins and write your own Integrate email services into your applications with Action Mailer Improve application responsiveness with background processing Create your own non-Active Record domain classes using Active Model Master Rails' utility classes and extensions in Active Support

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    It has no concept of classes, and you don't even need to define any objects in order to write code. But don't be fooled—JavaScript is an incredibly powerful and expressive object-oriented language that puts many design decisions right into your hands.In The Principles of Object-Oriented JavaScript, Nicholas C. Zakas thoroughly explores JavaScript's object-oriented nature, revealing the language's unique implementation of inheritance and other key characteristics. You'll learn: The difference between primitive and reference values What makes JavaScript functions so unique The various ways to create objects How to define your own constructors How to work with and understand prototypes Inheritance patterns for types and objects The Principles of Object-Oriented JavaScript will leave even experienced developers with a deeper understanding of JavaScript. Unlock the secrets behind how objects work in JavaScript so you can write clearer, more flexible, and more efficient code.

    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.

    It presents a learning journey, not definitive guidance. It describes the experiences of a development team with no prior CQRS proficiency in building, deploying (to Windows Azure), and maintaining a sample real-world, complex, enterprise system to showcase various CQRS and ES concepts, challenges, and techniques.The development team did not work in isolation; we actively sought input from industry experts and from a wide group of advisors to ensure that the guidance is both detailed and practical.The CQRS pattern and event sourcing are not mere simplistic solutions to the problems associated with large-scale, distributed systems. By providing you with both a working application and written guidance, we expect you’ll be well prepared to embark on your own CQRS journey.

    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!

    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

    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.

    Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most complex environments. Systems Performance: Enterprise and the Cloud focuses on Linux(R) and Unix(R) performance, while illuminating performance issues that are relevant to all operating systems. You'll gain deep insight into how systems work and perform, and learn methodologies for analyzing and improving system and application performance. Gregg presents examples from bare-metal systems and virtualized cloud tenants running Linux-based Ubuntu(R), Fedora(R), CentOS, and the illumos-based Joyent(R) SmartOS(TM) and OmniTI OmniOS(R). He systematically covers modern systems performance, including the "traditional" analysis of CPUs, memory, disks, and networks, and new areas including cloud computing and dynamic tracing. This book also helps you identify and fix the "unknown unknowns" of complex performance: bottlenecks that emerge from elements and interactions you were not aware of. The text concludes with a detailed case study, showing how a real cloud customer issue was analyzed from start to finish. Coverage includes - Modern performance analysis and tuning: terminology, concepts, models, methods, and techniques - Dynamic tracing techniques and tools, including examples of DTrace, SystemTap, and perf - Kernel internals: uncovering what the OS is doing - Using system observability tools, interfaces, and frameworks - Understanding and monitoring application performance - Optimizing CPUs: processors, cores, hardware threads, caches, interconnects, and kernel scheduling - Memory optimization: virtual memory, paging, swapping, memory architectures, busses, address spaces, and allocators - File system I/O, including caching - Storage devices/controllers, disk I/O workloads, RAID, and kernel I/O - Network-related performance issues: protocols, sockets, interfaces, and physical connections - Performance implications of OS and hardware-based virtualization, and new issues encountered with cloud computing - Benchmarking: getting accurate results and avoiding common mistakes This guide is indispensable for anyone who operates enterprise or cloud environments: system, network, database, and web admins; developers; and other professionals. For students and others new to optimization, it also provides exercises reflecting Gregg's extensive instructional experience.

    Readers will learn to understand object-oriented design with inheritance or composition, object aggregation and association, and the difference between interfaces and implementations. Readers will also become more efficient and better thinkers in terms of object-oriented development." This revised edition focuses on interoperability across various technologies, primarily using XML as the communication mechanism. A more detailed focus is placed on how business objects operate over networks, including client/server architectures and web services.

    And how to move all of this data becomes nearly as important as the data itself. If you� re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds.Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you� ll learn Kafka� s design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer.Understand publish-subscribe messaging and how it fits in the big data ecosystem.Explore Kafka producers and consumers for writing and reading messagesUnderstand Kafka patterns and use-case requirements to ensure reliable data deliveryGet best practices for building data pipelines and applications with KafkaManage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasksLearn the most critical metrics among Kafka� s operational measurementsExplore how Kafka� s stream delivery capabilities make it a perfect source for stream processing systems