Topics covered include:Basic version control commands and conceptsIntroduction to Distributed Version Control Systems (DVCS)Advanced branching workflowsStrengths and weaknesses of DVCS vs. centralized toolsBest practicesHow distributed version control works under the hoodFeaturing these open source version control tools:Apache SubversionMercurialGitVeracity

    "TCP/IP Illustrated, Volume 2" contains a thorough explanation of how TCP/IP protocols are implemented. There isn't a more practical or up-to-date bookothis volume is the only one to cover the de facto standard implementation from the 4.4BSD-Lite release, the foundation for TCP/IP implementations run daily on hundreds of thousands of systems worldwide. Combining 500 illustrations with 15,000 lines of real, working code, "TCP/IP Illustrated, Volume 2" uses a teach-by-example approach to help you master TCP/IP implementation. You will learn about such topics as the relationship between the sockets API and the protocol suite, and the differences between a host implementation and a router. In addition, the book covers the newest features of the 4.4BSD-Lite release, including multicasting, long fat pipe support, window scale, timestamp options, and protection against wrapped sequence numbers, and many other topics. Comprehensive in scope, based on a working standard, and thoroughly illustrated, this book is an indispensable resource for anyone working with TCP/IP.

    The preeminent expert in his field, Mr.Black draws upon years of experience as president of both theInternational and American Software Testing Qualifications boardsto offer this extensive resource of all the standards, methods, andtools you'll need.The book covers core testing concepts and thoroughly examinesthe best test management practices and tools of leading hardwareand software vendors. Step-by-step guidelines and real-worldscenarios help you follow all necessary processes and avoidmistakes.Producing high-quality computer hardware and software requirescareful, professional testing; Managing the Testing Process, Third Edition explains how to achieve that by following adisciplined set of carefully managed and monitored practices andprocessesThe book covers all standards, methods, and tools you need forprojects large and smallPresents the business case for testing products and reviews theauthor's latest test assessmentsTopics include agile testing methods, risk-based testing, IEEEstandards, ISTQB certification, distributed and outsourced testing, and moreOver 100 pages of new material and case studies have been addedto this new editionIf you're responsible for managing testing in the real world, Managing the Testing Process, Third Edition is the valuablereference and guide you need.

    Computer scientists have identified many techniques that a wide range of programs need, such as: Fuzzy pattern matching for text (identify misspellings!) Finding correlations in data Game-playing algorithms Predicting phenomena such as Web traffic Polynomial and spline fitting Using algorithms explained in this book, you too can carry out traditional programming tasks in a high-powered, efficient, easy-to-maintain manner with Perl.This book assumes a basic understanding of Perl syntax and functions, but not necessarily any background in computer science. The authors explain in a readable fashion the reasons for using various classic programming techniques, the kind of applications that use them, and -- most important -- how to code these algorithms in Perl.If you are an amateur programmer, this book will fill you in on the essential algorithms you need to solve problems like an expert. If you have already learned algorithms in other languages, you will be surprised at how much different (and often easier) it is to implement them in Perl. And yes, the book even has the obligatory fractal display program.There have been dozens of books on programming algorithms, some of them excellent, but never before has there been one that uses Perl.The authors include the editor of The Perl Journal and master librarian of CPAN; all are contributors to CPAN and have archived much of the code in this book there."This book was so exciting I lost sleep reading it." Tom Christiansen

    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.

    What sets this book apart is its focus on learning. The authors have made the content of OOAD accessible, usable for the practitioner." Ivar Jacobson, Ivar Jacobson Consulting"I just finished reading HF OOA&D and I loved it! The thing I liked most about this book was its focus on why we do OOA&D-to write great software!" Kyle Brown, Distinguished Engineer, IBM"Hidden behind the funny pictures and crazy fonts is a serious, intelligent, extremely well-crafted presentation of OO Analysis and Design. As I read the book, I felt like I was looking over the shoulder of an expert designer who was explaining to me what issues were important at each step, and why." Edward Sciore, Associate Professor, Computer Science Department, Boston College Tired of reading Object Oriented Analysis and Design books that only makes sense after you're an expert? You've heard OOA&D can help you write great software every time-software that makes your boss happy, your customers satisfied and gives you more time to do what makes you happy.But how?Head First Object-Oriented Analysis & Design shows you how to analyze, design, and write serious object-oriented software: software that's easy to reuse, maintain, and extend; software that doesn't hurt your head; software that lets you add new features without breaking the old ones. Inside you will learn how to:Use OO principles like encapsulation and delegation to build applications that are flexible Apply the Open-Closed Principle (OCP) and the Single Responsibility Principle (SRP) to promote reuse of your code Leverage the power of design patterns to solve your problems more efficiently Use UML, use cases, and diagrams to ensure that all stakeholders are communicating clearly to help you deliver the right software that meets everyone's needs.By exploiting how your brain works, Head First Object-Oriented Analysis & Design compresses the time it takes to learn and retain complex information. Expect to have fun, expect to learn, expect to be writing great software consistently by the time you're finished reading this!

    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

    Distributed Systems provides students of computer science and engineering with the skills they will need to design and maintain software for distributed applications. It will also be invaluable to software engineers and systems designers wishing to understand new and future developments in the field. From mobile phones to the Internet, our lives depend increasingly on distributed systems linking computers and other devices together in a seamless and transparent way. The fifth edition of this best-selling text continues to provide a comprehensive source of material on the principles and practice of distributed computer systems and the exciting new developments based on them, using a wealth of modern case studies to illustrate their design and development. The depth of coverage will enable readers to evaluate existing distributed systems and design new ones.

    Topics are broken down into three major conceptual pieces: Virtualization, Concurrency, and Persistence. Includes all major components of modern systems including scheduling, virtual memory management, disk subsystems and I/O, file systems, and even a short introduction to distributed systems.

    Some books try to give you copy-and-paste instructions for how to deal with every single system issue that may arise, but How Linux Works actually shows you how the Linux system functions so that you can come up with your own solutions. After a guided tour of filesystems, the boot sequence, system management basics, and networking, author Brian Ward delves into open-ended topics such as development tools, custom kernels, and buying hardware, all from an administrator's point of view. With a mixture of background theory and real-world examples, this book shows both "how" to administer Linux, and "why" each particular technique works, so that you will know how to make Linux work for you.

    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.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples