The book covers the main phases in the life cycle of design and implementation of a system, i.e., specification, model checking techniques for verification, analysis of properties, code generation, and execution of models. These techniques and their tool support are discussed in detail including practical issues. Amongst others, fundamental concepts such as composition, abstraction, and reusability of models, model verification, and verification of properties are systematically introduced.
The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.
The companion web site, algs4.cs.princeton.edu, containsAn online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material
The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.
Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.
Readers learn how to use a domain model to make a complex development effort more focused and dynamic. A core of best practices and standard patterns provides a common language for the development team. A shift in emphasis–refactoring not just the code but the model underlying the code–in combination with the frequent iterations of Agile development leads to deeper insight into domains and enhanced communication between domain expert and programmer. Domain-Driven Design then builds on this foundation, and addresses modeling and design for complex systems and larger organizations.Specific topics covered include:
With this book in hand, object-oriented developers, system analysts, and designers will have the guidance they need to organize and focus their work, create rich and useful domain models, and leverage those models into quality, long-lasting software implementations.
Inside, you'll learn about:
Interaction design and physical computingThe Arduino hardware and software development environmentBasics of electricity and electronicsPrototyping on a solderless breadboardDrawing a schematic diagram
And more. With inexpensive hardware and open-source software components that you can download free, getting started with Arduino is a snap. To use the introductory examples in this book, all you need is a USB Arduino, USB A-B cable, and an LED.
Join the tens of thousands of hobbyists who have discovered this incredible (and educational) platform. Written by the co-founder of the Arduino project, with illustrations by Elisa Canducci, Getting Started with Arduino gets you in on the fun! This 128-page book is a greatly expanded follow-up to the author's original short PDF that's available on the Arduino website.
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
In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization.
This book is divided into four sections:Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practicesPrinciples—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE)Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systemsManagement—Explore Google's best practices for training, communication, and meetings that your organization can use
Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You’ll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization’s goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures
The CWNA: Certified Wireless Network Administrator Official Study Guide: Exam CWNA-106 is the officially endorsed CWNA test prep for the leading wireless certification. Expert authors and CWNEs David D. Coleman and David A. Westcott guide readers through the skills and concepts candidates need to know for the exam, using hands-on methods to convey an in-depth understanding of wireless network administration. Readers should have a basic knowledge of Radio Frequency behavior, experience with WLAN hardware peripherals and protocols, and an interest in designing, installing, and managing wireless networks.
Wireless technology is taking over the tech industry, and the demand for competent, certified professionals is far outpacing the supply. A CWNA certification denotes advanced-level proficiency in the field, with a complete understanding of wireless LAN components, features, and function—but the only way to pass the exam is to truly understand the material, not just the talking points. The CWNA: Certified Wireless Network Administrator Official Study Guide thoroughly covers each exam objective, and includes review questions, assessment tests, and exercises to test your skills. Topics include:Radio Frequency technologies, regulations, and standards 802.11 protocols Network implementation and security 802.11 RF site surveying
Readers also get access to a suite of study tools including an electronic test engine with hundreds or practice test questions, electronic flashcards, exercise peripherals, and industry White Papers, which serve as valuable backup references. In preparing for the CWNA-106 exam, the ideal study guide should cover all of the exam topics in depth—CWNA: Certified Wireless Network Administrator Official Study Guide does just that, making it an excellent, comprehensive study guide.
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Author Lorin Hochstein shows you how to write playbooks (Ansible’s configuration management scripts), manage remote servers, and explore the tool’s real power: built-in declarative modules. You’ll discover that Ansible has the functionality you need and the simplicity you desire.Understand how Ansible differs from other configuration management systemsUse the YAML file format to write your own playbooksLearn Ansible’s support for variables and factsWork with a complete example to deploy a non-trivial applicationUse roles to simplify and reuse playbooksMake playbooks run faster with ssh multiplexing, pipelining, and parallelismDeploy applications to Amazon EC2 and other cloud platformsUse Ansible to create Docker images and deploy Docker containers
This highly versatile text provides mathematical background used in a wide variety of disciplines, including mathematics and mathematics education, computer science, biology, chemistry, engineering, communications, and business.
Some of the major features and strengths of this textbook
More than 1,600 exercises, ranging from elementary to challenging, are included with hints/answers to all odd-numbered exercises.
Descriptions of proof techniques are accessible and lively.
Students benefit from the historical discussions throughout the textbook.
Updated for the latest versions of this popular database, this edition covers many complex features that have been added to MySQL 5.0 and 5.1, including a section dedicated to stored procedures and triggers. After a brief introduction on installation and initial setup, the book explains: How to configure MySQL, such as setting the root passwordMySQL data types, including numerics, strings, dates, and complex typesSQL syntax, commands, data types, operators, and functionsArithmetic, comparison and logical operatorsAggregate and general functionsStored procedures and triggers, including procedure definition, procedure calls, procedure management, cursors, and triggersYou don't have time to stop and thumb through an exhaustive reference when you're hard at work. This portable and affordable guide is small enough to fit into your pocket, and gives you a convenient reference that you can consult anywhere. When you reach a sticking point and need to get to a solution quickly, the MySQL Pocket Reference is the book you want to have.
With refactoring, programmers can transform even the most chaotic software into well-designed systems that are far easier to evolve and maintain. What’s more, they can do it one step at a time, through a series of simple, proven steps. Now, there’s an authoritative and extensively updated version of Martin Fowler’s classic refactoring book that utilizes Ruby examples and idioms throughout–not code adapted from Java or any other environment.
The authors introduce a detailed catalog of more than 70 proven Ruby refactorings, with specific guidance on when to apply each of them, step-by-step instructions for using them, and example code illustrating how they work. Many of the authors’ refactorings use powerful Ruby-specific features, and all code samples are available for download.
Leveraging Fowler’s original concepts, the authors show how to perform refactoring in a controlled, efficient, incremental manner, so you methodically improve your code’s structure without introducing new bugs. Whatever your role in writing or maintaining Ruby code, this book will be an indispensable resource.
This book will help youUnderstand the core principles of refactoring and the reasons for doing it Recognize “bad smells” in your Ruby code Rework bad designs into well-designed code, one step at a time Build tests to make sure your refactorings work properly Understand the challenges of refactoring and how they can be overcome Compose methods to package code properly Move features between objects to place responsibilities where they fit best Organize data to make it easier to work with Simplify conditional expressions and make more effective use of polymorphism Create interfaces that are easier to understand and use Generalize more effectively Perform larger refactorings that transform entire software systems and may take months or years Successfully refactor Ruby on Rails code
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.Get started quickly with an R tutorial and hundreds of examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with R’s graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R
Inside, you’ll learn about:Interaction design and physical computing The Arduino hardware and software development environment Basics of electricity and electronics Prototyping on a solderless breadboard Drawing a schematic diagram
Getting started with Arduino is a snap. To use the introductory examples in this guide, all you need an Arduino Uno or earlier model, along with USB A-B cable and an LED. The easy-to-use Arduino development environment is free to download.
Join hundreds of thousands of hobbyists who have discovered this incredible (and educational) platform. Written by the co-founder of the Arduino project, Getting Started with Arduino gets you in on all the fun!
In Service Design Patterns, Rob Daigneau codifies proven design solutions for web services that follow the REST architectural style or leverage the SOAP/WSDL specifications. This catalogue identifies the fundamental topics in web service design and lists the common design patterns for each topic. All patterns identify the context in which they may be used, explain the constituent design elements, and explore the relative strengths and trade-offs. Code examples are provided to help you better understand how the patterns work but are kept general so that you can see how the solutions may be applied to disparate technologies that will inevitably change in the years to come.
This book will help readers answer the following questions:How do you create a web service API, what are the common API styles, and when should a particular style be used? How can clients and web services communicate, and what are the foundations for creating complex conversations in which multiple parties exchange data over extended periods of time? What are the options for implementing web service logic, and when should a particular approach be used? How can clients become less coupled to the underlying systems used by a service? How can information about a web service be discovered? How can generic functions like authentication, validation, caching, and logging be supported on the client or service? What changes to a service cause clients to break? What are the common ways to version a service? How can web services be designed to support the continuing evolution of business logic without forcing clients to constantly upgrade?
This book is an invaluable resource for enterprise architects, solution architects, and developers who use web services to create enterprise IT applications, commercial or open source products, and Software as a Service (SaaS) products that leverage emerging Cloud platforms.
You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—classification, collaborative filtering, and anomaly detection among others—to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you’ll find these patterns useful for working on your own data applications.
Patterns include:Recommending music and the Audioscrobbler data setPredicting forest cover with decision treesAnomaly detection in network traffic with K-means clusteringUnderstanding Wikipedia with Latent Semantic AnalysisAnalyzing co-occurrence networks with GraphXGeospatial and temporal data analysis on the New York City Taxi Trips dataEstimating financial risk through Monte Carlo simulationAnalyzing genomics data and the BDG projectAnalyzing neuroimaging data with PySpark and Thunder
The potential user base and the wide array of available high-performance devices makes Android an attractive target for aspiring game developers. Do you have an awesome idea for the next break-through mobile gaming title? Beginning Android Games will help you kick-start your project. This book will guide you through the process of making several example game apps using APIs available in new Android SDK and earlier SDK releases for Android smartphones and tablets:The fundamentals of game development and design suitable for Android smartphones and tablets The Android platform basics to apply those fundamentals in the context of making a game, including new File Manager system and better battery life management The design of 2D and 3D games and their successful implementation on the Android platform
This book lets developers see and use some Android SDK Jelly Bean; however, this book is structured so that app developers can use earlier Android SDK releases. This book is backward compatible like the Android SDK.
--Richard Mark Soley, Chairman and CEO, OMG
If you're like most software developers, you're building systems that are increasingly complex. Whether you're creating a desktop application or an enterprise system, complexity is the big hairy monster you must manage.
The Unified Modeling Language (UML) helps you manage this complexity. Whether you're looking to use UML as a blueprint language, a sketch tool, or as a programming language, this book will give you the need-to-know information on how to apply UML to your project. While there are plenty of books available that describe UML, Learning UML 2.0 will show you how to use it. Topics covered include:
Capturing your system's requirements in your model to help you ensure that your designs meet your users' needs
Modeling the parts of your system and their relationships
Modeling how the parts of your system work together to meet your system's requirements
Modeling how your system moves into the real world, capturing how your system will be deployed
Engaging and accessible, this book shows you how to use UML to craft and communicate your project's design. Russ Miles and Kim Hamilton have written a pragmatic introduction to UML based on hard-earned practice, not theory. Regardless of the software process or methodology you use, this book is the one source you need to get up and running with UML 2.0.
Russ Miles is a software engineer for General Dynamics UK, where he works with Java and Distributed Systems, although his passion at the moment is Aspect Orientation and, in particular, AspectJ. Kim Hamilton is a senior software engineer at Northrop Grumman, where she's designed and implemented a variety of systems including web applications and distributed systems, with frequent detours into algorithms development.
Inside the Machine, from the co-founder of the highly respected Ars Technica website, explains how microprocessors operate-what they do and how they do it. The book uses analogies, full-color diagrams, and clear language to convey the ideas that form the basis of modern computing. After discussing computers in the abstract, the book examines specific microprocessors from Intel, IBM, and Motorola, from the original models up through today's leading processors. It contains the most comprehensive and up-to-date information available (online or in print) on Intel's latest processors: the Pentium M, Core, and Core 2 Duo. Inside the Machine also explains technology terms and concepts that readers often hear but may not fully understand, such as "pipelining," "L1 cache," "main memory," "superscalar processing," and "out-of-order execution."
Includes discussion of:
* Parts of the computer and microprocessor
* Programming fundamentals (arithmetic instructions, memory accesses, control flow instructions, and data types)
* Intermediate and advanced microprocessor concepts (branch prediction and speculative execution)
* Intermediate and advanced computing concepts (instruction set architectures, RISC and CISC, the memory hierarchy, and encoding and decoding machine language instructions)
* 64-bit computing vs. 32-bit computing
* Caching and performance
Inside the Machine is perfect for students of science and engineering, IT and business professionals, and the growing community of hardware tinkerers who like to dig into the guts of their machines.
Designing Web Interfaces illustrates many patterns with examples from working websites. If you need to build or renovate a website to be truly interactive, this book gives you the principles for success.
This reference gives a quick and authoritative summary of the key concepts of DDD. It is not meant as a learning introduction to the subject. Eric Evans' original book and a handful of others explain DDD in depth from different perspectives. On the other hand, we often need to scan a topic quickly or get the gist of a particular pattern. That is the purpose of this reference. It is complementary to the more discursive books.
The starting point of this text was a set of excerpts from the original book by Eric Evans, Domain-Driven-Design: Tackling Complexity in the Heart of Software, 2004 - in particular, the pattern summaries, which were placed in the Creative Commons by Evans and the publisher, Pearson Education. In this reference, those original summaries have been updated and expanded with new content.
The practice and understanding of DDD has not stood still over the past decade, and Evans has taken this chance to document some important refinements. Some of the patterns and definitions have been edited or rewritten by Evans to clarify the original intent. Three patterns have been added, describing concepts whose usefulness and importance has emerged in the intervening years. Also, the sequence and grouping of the topics has been changed significantly to better emphasize the core principles.
This is an up-to-date, quick reference to DDD.
In three parts, this book explains how these services work and what it means to build an application the Microservices Way. You’ll explore a design-based approach to microservice architecture with guidance for implementing various elements. And you’ll get a set of recipes and practices for meeting practical, organizational, and cultural challenges to microservice adoption.Learn how microservices can help you drive business objectivesExamine the principles, practices, and culture that define microservice architecturesExplore a model for creating complex systems and a design process for building a microservice architectureLearn the fundamental design concepts for individual microservicesDelve into the operational elements of a microservices architecture, including containers and service discoveryDiscover how to handle the challenges of introducing microservice architecture in your organization
This updated second edition provides guidance for database developers, advanced configuration for system administrators, and an overview of the concepts and use cases for other people on your project. Ideal for NoSQL newcomers and experienced MongoDB users alike, this guide provides numerous real-world schema design examples.Get started with MongoDB core concepts and vocabularyPerform basic write operations at different levels of safety and speedCreate complex queries, with options for limiting, skipping, and sorting resultsDesign an application that works well with MongoDBAggregate data, including counting, finding distinct values, grouping documents, and using MapReduceGather and interpret statistics about your collections and databasesSet up replica sets and automatic failover in MongoDBUse sharding to scale horizontally, and learn how it impacts applicationsDelve into monitoring, security and authentication, backup/restore, and other administrative tasks
Rather than run through all possible scenarios, this pragmatic operations guide calls out what works, as demonstrated in critical deployments.Get a high-level overview of HDFS and MapReduce: why they exist and how they workPlan a Hadoop deployment, from hardware and OS selection to network requirementsLearn setup and configuration details with a list of critical propertiesManage resources by sharing a cluster across multiple groupsGet a runbook of the most common cluster maintenance tasksMonitor Hadoop clusters—and learn troubleshooting with the help of real-world war storiesUse basic tools and techniques to handle backup and catastrophic failure
"Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss:
How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes.
Important data warehouse technologies and practices.
Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouseDemystifies data vault modeling with beginning, intermediate, and advanced techniquesDiscusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0
By reading this definitive tutorial and reference, you'll gain the knowledge and experience to create stunning, cutting-edge Android apps that can make you money, while keeping you agile enough to respond to changes in the future.
Authors Ben Spivey and Joey Echeverria provide in-depth information about the security features available in Hadoop, and organize them according to common computer security concepts. You’ll also get real-world examples that demonstrate how you can apply these concepts to your use cases.Understand the challenges of securing distributed systems, particularly HadoopUse best practices for preparing Hadoop cluster hardware as securely as possibleGet an overview of the Kerberos network authentication protocolDelve into authorization and accounting principles as they apply to HadoopLearn how to use mechanisms to protect data in a Hadoop cluster, both in transit and at restIntegrate Hadoop data ingest into enterprise-wide security architectureEnsure that security architecture reaches all the way to end-user access
Beginning with digital logic gates and progressing to the design of combinational and sequential circuits, this book uses these fundamental building blocks as the basis for designing an ARM processor. SystemVerilog and VHDL are integrated throughout the text in examples illustrating the methods and techniques for CAD-based circuit design. The companion website includes a chapter on I/O systems with practical examples that show how to use the Raspberry Pi computer to communicate with peripheral devices such as LCDs, Bluetooth radios, and motors.
This book will be a valuable resource for students taking a course that combines digital logic and computer architecture or students taking a two-quarter sequence in digital logic and computer organization/architecture.Covers the fundamentals of digital logic design and reinforces logic concepts through the design of an ARM microprocessor.Features side-by-side examples of the two most prominent Hardware Description Languages (HDLs)—SystemVerilog and VHDL—which illustrate and compare the ways each can be used in the design of digital systems.Includes examples throughout the text that enhance the reader’s understanding and retention of key concepts and techniques.The Companion website includes a chapter on I/O systems with practical examples that show how to use the Raspberry Pi computer to communicate with peripheral devices such as LCDs, Bluetooth radios, and motors. The Companion website also includes appendices covering practical digital design issues and C programming as well as links to CAD tools, lecture slides, laboratory projects, and solutions to exercises.
If you administer a DNS system or are thinking about running one, or if you need to upgrade to support IPv6 DNS, need to secure a DNS for zone transfer, dynamic update, or other reasons, or if you need to implement DNSSEC, or simply want to understand the DNS system, then this book provides you with a single point of reference. Pro DNS and BIND starts with simple concepts, then moves on to full security-aware DNSSEC configurations. Various features, parameters, and resource records are described and, in the majority of cases, illustrated with one or more examples.
The book contains a complete reference to zone files, Resource Records, and BINDs configuration file parameters. You can treat the book as as a simple paint-by-numbers guide to everything from a simple caching DNS, to the most complex secure DNS (DNSSEC) implementation. Background information is still included for when you need to know what to do and why you have to do it, and so that you can modify processes to meet your unique needs.
Concise, readable, and actionable, Domain-Driven Design Distilled never buries you in detail–it focuses on what you need to know to get results. Vaughn Vernon, author of the best-selling Implementing Domain-Driven Design, draws on his twenty years of experience applying DDD principles to real-world situations. He is uniquely well-qualified to demystify its complexities, illuminate its subtleties, and help you solve the problems you might encounter.
Vernon guides you through each core DDD technique for building better software. You’ll learn how to segregate domain models using the powerful Bounded Contexts pattern, to develop a Ubiquitous Language within an explicitly bounded context, and to help domain experts and developers work together to create that language. Vernon shows how to use Subdomains to handle legacy systems and to integrate multiple Bounded Contexts to define both team relationships and technical mechanisms.
Domain-Driven Design Distilled brings DDD to life. Whether you’re a developer, architect, analyst, consultant, or customer, Vernon helps you truly understand it so you can benefit from its remarkable power.
Coverage includesWhat DDD can do for you and your organization–and why it’s so important The cornerstones of strategic design with DDD: Bounded Contexts and Ubiquitous Language Strategic design with Subdomains Context Mapping: helping teams work together and integrate software more strategically Tactical design with Aggregates and Domain Events Using project acceleration and management tools to establish and maintain team cadence
Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shellLeverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlibUse one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and StormLearn how to deploy interactive, batch, and streaming applicationsConnect to data sources including HDFS, Hive, JSON, and S3Master advanced topics like data partitioning and shared variables
By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
This book offers practical answers to some of the hardest questions faced by PL/SQL developers, including:What is the best way to write the SQL logic in my application code?
How should I write my packages so they can be leveraged by my entire team of developers?
How can I make sure that all my team's programs handle and record errors consistently?Oracle PL/SQL Best Practices summarizes PL/SQL best practices in nine major categories: overall PL/SQL application development; programming standards; program testing, tracing, and debugging; variables and data structures; control logic; error handling; the use of SQL in PL/SQL; building procedures, functions, packages, and triggers; and overall program performance.
This book is a concise and entertaining guide that PL/SQL developers will turn to again and again as they seek out ways to write higher quality code and more successful applications.
"This book presents ideas that make the difference between a successful project and one that never gets off the ground. It goes beyond just listing a set of rules, and provides realistic scenarios that help the reader understand where the rules come from. This book should be required reading for any team of Oracle database professionals."
--Dwayne King, President, KRIDAN Consulting
Implementations, as well as interesting, real-world examples of each data structure and algorithm, are included.
Using both a programming style and a writing style that are exceptionally clean, Kyle Loudon shows you how to use such essential data structures as lists, stacks, queues, sets, trees, heaps, priority queues, and graphs. He explains how to use algorithms for sorting, searching, numerical analysis, data compression, data encryption, common graph problems, and computational geometry. And he describes the relative efficiency of all implementations. The compression and encryption chapters not only give you working code for reasonably efficient solutions, they offer explanations of concepts in an approachable manner for people who never have had the time or expertise to study them in depth.
Anyone with a basic understanding of the C language can use this book. In order to provide maintainable and extendible code, an extra level of abstraction (such as pointers to functions) is used in examples where appropriate. Understanding that these techniques may be unfamiliar to some programmers, Loudon explains them clearly in the introductory chapters.
Contents include:PointersRecursionAnalysis of algorithmsData structures (lists, stacks, queues, sets, hash tables, trees, heaps, priority queues, graphs)Sorting and searchingNumerical methodsData compressionData encryptionGraph algorithmsGeometric algorithms
This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.
This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers.New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and moreIncreased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelismTwo new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other.
How is Office for iPad different from Office on your Mac or PC? Which features do the Office for iPad apps have, which do they lack, and how can you work around their limitations? How can you share your files among the different versions of Office? How quickly can you work without the physical keyboard and keyboard shortcuts you're used to -- and which keyboard shortcuts can you use if you connect a hardware keyboard to your iPad?
Whether you plan to write a few letters or your dissertation, run your home office away from home, or use your iPad for daily business, Pro Office for iPad will show you how to get the most out of Word, Excel, and other Office apps on your iPad. Enjoy your new freedom and still be as productive as ever with the skills and techniques you'll learn in Pro Office for iPad.
OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, iPads, iPods, and Mac OS X servers and clients. Then, you’ll expand your horizons to examine Mac OS X and iOS system architecture. Understanding Apple’s operating systems will allow you to write efficient device drivers, such as those covered in the book, using I/O Kit.
With OS X and iOS Kernel Programming, you’ll:Discover classical kernel architecture topics such as memory management and thread synchronization Become well-versed in the intricacies of the kernel development process by applying kernel debugging and profiling tools Learn how to deploy your kernel-level projects and how to successfully package them Write code that interacts with hardware devices Examine easy to understand example code that can also be used in your own projects Create network filters
Whether you’re a hobbyist, student, or professional engineer, turn to OS X andiOS Kernel Programming and find the knowledge you need to start developing
In this third edition of a widely acclaimed resource, three networking experts share their extensive experience, teaching you the cabling skills you need to build a reliable, efficient, and cost-effective network cabling infrastructure. As you master these techniques, you'll learn to avoid common pitfalls and troubleshoot problems as quickly as they arise. Coverage includes:Choosing the right cables and components for your network architecture and topology Avoiding unnecessary and unexpected costs Understanding the current limitations of data communications and network cabling Understanding how laws and building codes constrain cabling Understanding the function and importance of universal cabling standards Determining when you have a cabling-related network problem Assembling a complete cabling toolkit Integrating voice and data on the same cable system Setting up an infrastructure in which desktops, printers, copiers, and other nodes share cabling Understanding issues of bandwidth, impedance, resistance, attenuation, crosstalk, capacitance, propagation, delay, and delay skew Working effectively with USB and Firewire Knowing when to discard legacy cabling and begin anew Documenting your cabling Creating an RFP and selecting a vendor
See Additional Notes for instructions to download the highly interactive PC software. Used in thousands of schools and colleges worldwide the software is designed to work as an interactive textbook on your PC screen.
Comprising hundreds of menu selected colourful topics where the graphic images (from your eBook) are brought to life for every value change along with many additional learning software features.
A combined eBook and educational software package at a tiny fraction of the previously published price.
Chapters (958 topics): - Introduction, Electronics, Basic Electronics, DC Current Flow, Resistor Value Test, Simple DC Circuits, Types of Switching, Variable Voltages, Ohm's Law, DC Voltage, DC Current, Series/Parallel Resistors, AC Measurements, AC Voltage and Current, AC Theory, RCL Series Circuits, RCL Parallel Circuits, Capacitance, Capacitors, Inductance, Inductors, Impedance, Radio and Communication, Tuned Circuits, Attenuators, Passive Filters, Active Filters, Oscillators, Circuit Theorems, Complex Numbers, DC Power, AC Power, Silicon Controlled Rectifier, Power Supplies, Voltage Regulation, Magnetism, Electric Machines, Transformers, Three Phase Systems, Energy Transfer and Cost, Atomic Structures, Diode Theory, Diode Applications, Transistor Theory, Bipolar Transistor, Transistor Configurations, Active Transistor Circuits, Field Effect Transistors, Basic Operational Amplifier, Op-Amp Theory, Op-Amp Applications, Sum and Difference Amp, Analogue Multi-meter, Measurement, Component Testing, PIC Micro, PICa(R) Microcontroller, PICa(R) Architecture, PICa(R) Analogue to Digital, PICa(R) Byte Orientated Instructions, PICa(R) Bit Orientated Instructions, PICa(R) Literal and Control Instructions, Mechanics, Area, Surface Area and Symmetry, Volume, Compound Measures, Geometry, Motion, Machines, Optics, Computing, Hardware Devices, Data Structures, Data Files, Computer Systems, Data Handling, System Development, Computer Programming, Data Analysis, Binary Numbers, Binary Arithmetic, Digital, Logic Gates 1., Logic Gates 2., Logic Families, Flip Flops, Combinational Logic, Counters, Counting, Shift Registers, 555 Timer, Logic Interfacing, Boolean and DeMorgan's, Microprocessor, Micro-Computer, Data/Address Bus, Memory Addressing, Arithmetic and Logic Unit, Clock and Reset, Instructions and Control, Memory Cells, Microprocessor Memory, Addressing Modes, Instructions Set 1., Instructions Set 2., Instructions Set 3., Mathematics, Number Systems, Number Conversion, Number Types, Compound Measures, Roots, Angles and Parallels, Triangle Ratios, Triangle Angles, Percentages, Ratios, Fractions, Vectors, Circle Angles, Laws, Algebra 0., Algebra 1., Algebra 2., Mathematical Rules, Powers and Indices, Simplifying, Equations, Graphing, Slope and Translation, Curves and Angle Conversion, Personal Finance, Additional Notes.
This book is dedicated to all the machine learning and deep learning enthusiasts, data scientists, researchers, and even students who want to perform more accurate, fast machine learning operations with TensorFlow. Those with basic knowledge of programming (Python and C/C++) and math concepts who want to be introduced to the topics of machine learning will find this book useful.What You Will LearnInstall and adopt TensorFlow in your Python environment to solve mathematical problemsGet to know the basic machine and deep learning conceptsTrain and test neural networks to fit your data modelMake predictions using regression algorithmsAnalyze your data with a clustering procedureDevelop algorithms for clustering and data classificationUse GPU computing to analyze big dataIn Detail
Google's TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural networks.
This book takes you through the practical software implementation of various machine learning techniques with TensorFlow. In the first few chapters, you'll gain familiarity with the framework and perform the mathematical operations required for data analysis. As you progress further, you'll learn to implement various machine learning techniques such as classification, clustering, neural networks, and deep learning through practical examples.
By the end of this book, you'll have gained hands-on experience of using TensorFlow and building classification, image recognition systems, language processing, and information retrieving systems for your application.Style and approach
Get quickly up and running with TensorFlow using this fast-paced guide. You will get to know everything that can be done with TensorFlow and we'll show you how to implement it in your environment. The examples in the book are from the core of the computation industry—something you can connect to and will find familiar.
Whether it's called physical computing, ubiquitous computing, or the Internet of Things, it's a hot topic in technology: how to channel your inner Steve Jobs and successfully combine hardware, embedded software, web services, electronics, and cool design to create cutting-edge devices that are fun, interactive, and practical. If you'd like to create the next must-have product, this unique book is the perfect place to start.
Both a creative and practical primer, it explores the platforms you can use to develop hardware or software, discusses design concepts that will make your products eye-catching and appealing, and shows you ways to scale up from a single prototype to mass production.Helps software engineers, web designers, product designers, and electronics engineers start designing products using the Internet-of-Things approach Explains how to combine sensors, servos, robotics, Arduino chips, and more with various networks or the Internet, to create interactive, cutting-edge devices Provides an overview of the necessary steps to take your idea from concept through production
If you'd like to design for the future, Designing the Internet of Things is a great place to start.