Design, develop, and master efficient Power BI solutions for impactful business insights Key Features *Get to grips with the fundamentals of Microsoft Power BI *Combine data from multiple sources, create visuals, and publish reports across platforms *Understand Power BI concepts with real-world use cases Book Description Microsoft Power BI Complete Reference Guide gets you started with business intelligence by showing you how to install the Power BI toolset, design effective data models, and build basic dashboards and visualizations that make your data come to life. In this Learning Path, you will learn to create powerful interactive reports by visualizing your data and learn visualization styles, tips and tricks to bring your data to life. You will be able to administer your organization's Power BI environment to create and share dashboards. You will also be able to streamline deployment by implementing security and regular data refreshes. Next, you will delve deeper into the nuances of Power BI and handling projects. You will get acquainted with planning a Power BI project, development, and distribution of content, and deployment. You will learn to connect and extract data from various sources to create robust datasets, reports, and dashboards. Additionally, you will learn how to format reports and apply custom visuals, animation and analytics to further refine your data. By the end of this Learning Path, you will learn to implement the various Power BI tools such as on-premises gateway together along with staging and securely distributing content via apps. This Learning Path includes content from the following Packt products: *Microsoft Power BI Quick Start Guide by Devin Knight et al. *Mastering Microsoft Power BI by Brett Powell What you will learn *Connect to data sources using both import and DirectQuery options *Leverage built-in and custom visuals to design effective reports *Administer a Power BI cloud tenant for your organization *Deploy your Power BI Desktop files into the Power BI Report Server *Build efficient data retrieval and transformation processes Who this book is for Microsoft Power BI Complete Reference Guide is for those who want to learn and use the Power BI features to extract maximum information and make intelligent decisions that boost their business. If you have a basic understanding of BI concepts and want to learn how to apply them using Microsoft Power BI, then Learning Path is for you. It consists of real-world examples on Power BI and goes deep into the technical issues, covers additional protocols, and much more.

Implement Business Central and explore methods to upgrade to NAV 2018 Key Features *Learn the key roles of Dynamics NAV partner and the roles within your customer's organization *Create configuration packages and perform data migration *Explore Microsoft Dynamics 365 Business Central to use Dynamics NAV 2018 functionalities in the Cloud Book Description Microsoft Dynamics Business Central is a full business solution suite and a complete ERP solution, which contains a robust set of development tools; these tools can help you to gain control over your business and can simplify supply chains, manufacturing, and operations. Implementing Microsoft Dynamics 365 Business Central On-Premise covers the latest features of Dynamics Business Central and NAV from the end users' and developers' perspectives. It also provides an insight into different tools available for implementation, whether it's a new installation or migrating from the previous version of Dynamics NAV. This book will take you from an introduction to Dynamics NAV 2018 through to exploring all the techniques related to implementation and migration. You will also learn to expand functionalities within your existing Microsoft Dynamics NAV installation, perform data analysis, and implement free third-party add-ons to your existing installation. As you progress through the book, you will learn to work with third-party add-on tools. In the concluding chapters, you will explore Dynamics 365 Business Central, the new Cloud solution based on the Microsoft NAV platform, and techniques for using Docker and Sandbox to develop applications. By the end of the book, you will have gained a deep understanding of the key components for successful Dynamics NAV implementation for an organization. What you will learn *Explore new features introduced in Microsoft Dynamics NAV 2018 *Migrate to Microsoft Dynamics NAV 2018 from previous versions *Learn abstract techniques for data analysis, reporting, and debugging *Install, configure, and use additional tools for business intelligence, document management, and reporting *Discover Dynamics 365 Business Central and several other Microsoft services *Utilize different tools to develop applications for Business Central Who this book is for Implementing Microsoft Dynamics 365 Business Central On-Premise is for Dynamics NAV partners and end users who want to know everything about Dynamics NAV implementation. This book is for you if you want to be a project manager or get involved with Dynamics NAV, but do not have the expertise to write code yourself. This book can also help you to understand the need to move to Business Central and its advantages.

A definitive guide on frontend development with Angular from design to deployment Key Features *Develop web applications from scratch using Angular and TypeScript *Explore reactive programming principles and RxJS to develop and test apps easily *Study continuous integration and deployment on the AWS cloud Book Description If you have been burnt by unreliable JavaScript frameworks before, you will be amazed by the maturity of the Angular platform. Angular enables you to build fast, efficient, and real-world web apps. In this Learning Path, you'll learn Angular and to deliver high-quality and production-grade Angular apps from design to deployment. You will begin by creating a simple fitness app, using the building blocks of Angular, and make your final app, Personal Trainer, by morphing the workout app into a full-fledged personal workout builder and runner with an advanced directive building - the most fundamental and powerful feature of Angular. You will learn the different ways of architecting Angular applications using RxJS, and some of the patterns that are involved in it. Later you’ll be introduced to the router-first architecture, a seven-step approach to designing and developing mid-to-large line-of-business apps, along with popular recipes. By the end of this book, you will be familiar with the scope of web development using Angular, Swagger, and Docker, learning patterns and practices to be successful as an individual developer on the web or as a team in the Enterprise. This Learning Path includes content from the following Packt products: *Angular 6 by Example by Chandermani Arora, Kevin Hennessy *Architecting Angular Applications with Redux, RxJS, and NgRx by Christoffer Noring *Angular 6 for Enterprise-Ready Web Applications by Doguhan Uluca What you will learn *Develop web applications from scratch using Angular and TypeScript *Explore reactive programming principles, RxJS to develop and test apps efficiently *Study continuous integration and deployment your Angular app on the AWS cloud Who this book is for If you're a JavaScript or frontend developer looking to gain comprehensive experience of using Angular for end-to-end enterprise-ready applications, this Learning Path is for you.

Understand, explore, and effectively present data using the powerful data visualization techniques of Python Key Features *Use the power of Pandas and Matplotlib to easily solve data mining issues *Understand the basics of statistics to build powerful predictive data models *Grasp data mining concepts with helpful use-cases and examples Book Description Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models. By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional. This Learning Path includes content from the following Packt products: *Statistics for Machine Learning by Pratap Dangeti *Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim *Pandas Cookbook by Theodore Petrou What you will learn *Understand the statistical fundamentals to build data models *Split data into independent groups *Apply aggregations and transformations to each group *Create impressive data visualizations *Prepare your data and design models *Clean up data to ease data analysis and visualization *Create insightful visualizations with Matplotlib and Seaborn *Customize the model to suit your own predictive goals Who this book is for If you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.

Explore C# and the .NET Core framework to create applications and optimize them with ASP.NET Core 2 Key Features *Get to grips with multi-threaded, concurrent, and asynchronous programming in C# and .NET Core *Develop modern, cross-platform applications with .NET Core 2.0 and C# 7.0 *Create efficient web applications with ASP.NET Core 2. Book Description C# is a widely used programming language, thanks to its easy learning curve, versatility, and support for modern paradigms. The language is used to create desktop apps, background services, web apps, and mobile apps. .NET Core is open source and compatible with Mac OS and Linux. There is no limit to what you can achieve with C# and .NET Core. This Learning Path begins with the basics of C# and object-oriented programming (OOP) and explores features of C#, such as tuples, pattern matching, and out variables. You will understand.NET Standard 2.0 class libraries and ASP.NET Core 2.0, and create professional websites, services, and applications. You will become familiar with mobile app development using Xamarin.Forms and learn to develop high-performing applications by writing optimized code with various profiling techniques. By the end of C# 7 and .NET: Designing Modern Cross-platform Applications, you will have all the knowledge required to build modern, cross-platform apps using C# and .NET. This Learning Path includes content from the following Packt products: *C# 7.1 and .NET Core 2.0 - Modern Cross-Platform Development - Third Edition by Mark J. Price *C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan What you will learn *Explore ASP.NET Core to create professional web applications *Master OOP with C# to increase code reusability and efficiency *Protect your data using encryption and hashing *Measure application performance using BenchmarkDotNet *Use design techniques to increase your application’s performance *Learn memory management techniques in .NET Core *Understand tools and techniques to monitor application performance Who this book is for This Learning Path is designed for developers who want to gain a solid foundation in C# and .NET Core, and want to build cross-platform applications. To gain maximum benefit from this Learning Path, you must have basic knowledge of C#.

Explore and understand data with the powerful data visualization techniques of Tableau, and then communicate insights in powerful ways Key Features *Apply best practices in data visualization and chart types exploration *Explore the latest version of Tableau Desktop with hands-on examples *Understand the fundamentals of Tableau storytelling Book Description Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You’ll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. This Learning Path includes content from the following Packt products: *Learning Tableau 10 - Second Edition by N. Milligan *Getting Started with Tableau 2018.x by Tristan Guillevin What you will learn *Build effective visualizations, dashboards, and story points *Build basic to more advanced charts with step-by-step recipes *Become familiar row-level, aggregate, and table calculations *Dig deep into data with clustering and distribution models *Prepare and transform data for analysis *Leverage Tableau’s mapping capabilities to visualize data *Use data storytelling techniques to aid decision making strategy Who this book is for Tableau 10 Complete Reference is designed for anyone who wants to understand their data better and represent it in an effective manner. It is also used for BI professionals and data analysts who want to do better at their jobs.

Build powerful data analytics applications with this business intelligence tool and overcome all your business challenges Key Features *Master time-saving techniques and make your QlikView development more efficient *Perform geographical analysis and sentiment analysis in your QlikView applications *Explore advanced QlikView techniques, tips, and tricks to deliver complex business requirements Book Description QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and present it as impactful and engaging visualizations. Each chapter in this Learning Path starts with an understanding of a business requirement and its associated data model and then helps you create insightful analysis and data visualizations around it. You will look at problems that you might encounter while visualizing complex data insights using QlikView, and learn how to troubleshoot these and other not-so-common errors. This Learning Path contains real-world examples from a variety of business domains, such as sales, finance, marketing, and human resources. With all the knowledge that you gain from this Learning Path, you will have all the experience you need to implement your next QlikView project like a pro. This Learning Path includes content from the following Packt products: *QlikView for Developers by Miguel ?ngel García, Barry Harmsen *Mastering QlikView by Stephen Redmond *Mastering QlikView Data Visualization by Karl Pover What you will learn *Deliver common business requirements using advanced techniques *Load data from disparate sources to build associative data models *Understand when to apply more advanced data visualization *Utilize the built-in aggregation functions for complex calculations *Build a data architecture that supports scalable QlikView deployments *Troubleshoot common data visualization errors in QlikView *Protect your QlikView applications and data Who this book is for This Learning Path is designed for developers who want to go beyond their technical knowledge of QlikView and understand how to create analysis and data visualizations that solve real business needs. To grasp the concepts explained in this Learning Path, you should have a basic understanding of the common QlikView functions and some hands-on experience with the tool.

Get to grips with the unified, highly scalable distributed storage system and learn how to design and implement it. Key Features * Explore Ceph's architecture in detail * Implement a Ceph cluster successfully and gain deep insights into its best practices * Leverage the advanced features of Ceph, including erasure coding, tiering, and BlueStore Book Description This Learning Path takes you through the basics of Ceph all the way to gaining in-depth understanding of its advanced features. You’ll gather skills to plan, deploy, and manage your Ceph cluster. After an introduction to the Ceph architecture and its core projects, you’ll be able to set up a Ceph cluster and learn how to monitor its health, improve its performance, and troubleshoot any issues. By following the step-by-step approach of this Learning Path, you’ll learn how Ceph integrates with OpenStack, Glance, Manila, Swift, and Cinder. With knowledge of federated architecture and CephFS, you’ll use Calamari and VSM to monitor the Ceph environment. In the upcoming chapters, you’ll study the key areas of Ceph, including BlueStore, erasure coding, and cache tiering. More specifically, you’ll discover what they can do for your storage system. In the concluding chapters, you will develop applications that use Librados and distributed computations with shared object classes, and see how Ceph and its supporting infrastructure can be optimized. By the end of this Learning Path, you'll have the practical knowledge of operating Ceph in a production environment. This Learning Path includes content from the following Packt products: * Ceph Cookbook by Michael Hackett, Vikhyat Umrao and Karan Singh * Mastering Ceph by Nick Fisk * Learning Ceph, Second Edition by Anthony D'Atri, Vaibhav Bhembre and Karan Singh What you will learn * Understand the benefits of using Ceph as a storage solution * Combine Ceph with OpenStack, Cinder, Glance, and Nova components * Set up a test cluster with Ansible and virtual machine with VirtualBox * Develop solutions with Librados and shared object classes * Configure BlueStore and see its interaction with other configurations * Tune, monitor, and recover storage systems effectively * Build an erasure-coded pool by selecting intelligent parameters Who this book is for If you are a developer, system administrator, storage professional, or cloud engineer who wants to understand how to deploy a Ceph cluster, this Learning Path is ideal for you. It will help you discover ways in which Ceph features can solve your data storage problems. Basic knowledge of storage systems and GNU/Linux will be beneficial.

Leverage the power of Kubernetes to build an efficient software delivery pipeline. Key Features * Learn about DevOps, containers, and Kubernetes all within one handy book * A practical guide to container management and orchestration * Learn how to monitor, log, and troubleshoot your Kubernetes applications Book Description Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure. What you will learn * Learn fundamental and advanced DevOps skills and tools * Get a comprehensive understanding of containers * Dockerize an application * Administrate and manage Kubernetes cluster * Extend the cluster functionality with custom resources * Understand Kubernetes network and service mesh * Implement Kubernetes logging and monitoring * Manage Kubernetes services in Amazon Web Services, Google Cloud Platform,and Microsoft Azure Who this book is for This book is for anyone who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills are required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced, you can get a deeper understanding of all the tools and technique described in the book.

Create distributed applications with clever design patterns to solve complex problems Key Features * Set up and run distributed algorithms on a cluster using Dask and PySpark * Master skills to accurately implement concurrency in your code * Gain practical experience of Python design patterns with real-world examples Book Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: * Python High Performance - Second Edition by Gabriele Lanaro * Mastering Concurrency in Python by Quan Nguyen * Mastering Python Design Patterns by Sakis Kasampalis What you will learn * Use NumPy and pandas to import and manipulate datasets * Achieve native performance with Cython and Numba * Write asynchronous code using asyncio and RxPy * Design highly scalable programs with application scaffolding * Explore abstract methods to maintain data consistency * Clone objects using the prototype pattern * Use the adapter pattern to make incompatible interfaces compatible * Employ the strategy pattern to dynamically choose an algorithm Who this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.

Create responsive eLearning content, including quizzes, demonstrations, simulations and Virtual Reality projects that fit on any device with Adobe Captivate 2019 Key Features * Build responsive, interactive and highly engaging eLearning content with Adobe Captivate 2019 * Build Virtual Reality eLearning experiences with Adobe Captivate 2019 * Assess your student knowledge with interactive and random quizzes * Seamlessly integrate your eLearning content with any SCORM or xAPI compliant LMS Book Description Adobe Captivate is used to create highly engaging, interactive, and responsive eLearning content. This book takes you through the production of a few pieces of eLearning content, covering all the project types and workflows of Adobe Captivate. First, you will learn how to create a typical interactive Captivate project. This will give you the opportunity to review all Captivate objects and uncover the application's main tools. Then, you will use the built-in capture engine of Captivate to create an interactive software simulation and a Video Demo that can be published as an MP4 video. Then, you will approach the advanced responsive features of Captivate to create a project that can be viewed on any device. And finally, you will immerse your learners in a 360o environment by creating Virtual Reality projects of Adobe Captivate. At the end of the book, you will empower your workflow and projects with the newer and most advanced features of the application, including variables, advanced actions, JavaScript, and using Captivate 2019 with other applications. If you want to produce high quality eLearning content using a wide variety of techniques, implement eLearning in your company, enable eLearning on any device, assess the effectiveness of the learning by using extensive Quizzing features, or are simply interested in eLearning, this book has you covered! What you will learn * Learn how to use the objects in Captivate to build professional eLearning content * Enhance your projects by adding interactivity, animations, and more * Add multimedia elements, such as audio and video, to create engaging learning experiences * Use themes to craft a unique visual experience * Use question slides to create SCORM-compliant quizzes that integrate seamlessly with your LMS * Make your content fit any device with responsive features of Captivate * Create immersive 360° experiences with Virtual Reality projects of Captivate 2019 * Integrate Captivate with other applications (such as PowerPoint and Photoshop) to establish a professional eLearning production workflow * Publish your project in a wide variety of formats including HTML5 and Flash Who this book is for If you are a teacher, instructional designer, eLearning developer, or human resources manager who wants to implement eLearning, then this book is for you. A basic knowledge of your OS is all it takes to create the next generation of responsive eLearning content.

Learn how to run new and old applications in Docker containers on Windows - modernizing the architecture, improving security and maximizing efficiency. Key Features * Run .NET Framework and .NET Core apps in Docker containers for efficiency, security and portability * Design distributed containerized apps, using enterprise-grade open source software from Docker Hub * Build a CI/CD pipeline with Docker, going from source to a production Docker Swarm in the cloud Book Description Docker on Windows, Second Edition teaches you all you need to know about Docker on Windows, from the 101 to running highly-available workloads in production. You’ll be guided through a Docker journey, starting with the key concepts and simple examples of .NET Framework and .NET Core apps in Docker containers on Windows. Then you’ll learn how to use Docker to modernize the architecture and development of traditional ASP.NET and SQL Server apps. The examples show you how to break up legacy monolithic applications into distributed apps and deploy them to a clustered environment in the cloud, using the exact same artifacts you use to run them locally. You’ll see how to build a CI/CD pipeline which uses Docker to compile, package, test and deploy your applications. To help you move confidently to production, you’ll learn about Docker security, and the management and support options. The book finishes with guidance on getting started with Docker in your own projects. You’ll walk through some real-world case studies for Docker implementations, from small-scale on-premises apps to very large-scale apps running on Azure. What you will learn * Understand key Docker concepts: images, containers, registries and swarms * Run Docker on Windows 10, Windows Server 2019, and in the cloud * Deploy and monitor distributed solutions across multiple Docker containers * Run containers with high availability and failover with Docker Swarm * Master security in-depth with the Docker platform, making your apps more secure * Build a Continuous Deployment pipeline, running Jenkins and Git in Docker * Debug applications running in Docker containers using Visual Studio * Plan the adoption of Docker in your organization Who this book is for If you want to modernize an old monolithic application without rewriting it, smooth the deployment to production, or move to DevOps or the cloud, then Docker is the enabler for you. This book gives you a solid grounding in Docker so you can confidently approach all of these scenarios.

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key Features * Discover best practices for engineering and maintaining OpenCV projects * Explore important deep learning tools for image classification * Understand basic image matrix formats and filters Book Description OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: * Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá * Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendon?a, and Prateek Joshi What you will learn * Stay up-to-date with algorithmic design approaches for complex computer vision tasks * Work with OpenCV's most up-to-date API through various projects * Understand 3D scene reconstruction and Structure from Motion (SfM) * Study camera calibration and overlay augmented reality (AR) using the ArUco module * Create CMake scripts to compile your C++ application * Explore segmentation and feature extraction techniques * Remove backgrounds from static scenes to identify moving objects for surveillance * Work with new OpenCV functions to detect and recognize text with Tesseract Who this book is for If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.

Discover practical solutions for a wide range of real-world network programming tasks About This Book ? Solve real-world tasks in the area of network programming, system/networking administration, network monitoring, and more. ? Familiarize yourself with the fundamentals and functionalities of SDN ? Improve your skills to become the next-gen network engineer by learning the various facets of Python programming Who This Book Is For This book is for network engineers, system/network administrators, network programmers, and even web application developers who want to solve everyday network-related problems. If you are a novice, you will develop an understanding of the concepts as you progress with this book. What You Will Learn ? Develop TCP/IP networking client/server applications ? Administer local machines' IPv4/IPv6 network interfaces ? Write multi-purpose efficient web clients for HTTP and HTTPS protocols ? Perform remote system administration tasks over Telnet and SSH connections ? Interact with popular websites via web services such as XML-RPC, SOAP, and REST APIs ? Monitor and analyze major common network security vulnerabilities ? Develop Software-Defined Networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX Controllers ? Emulate simple and complex networks with Mininet and its extensions for network and systems emulations ? Learn to configure and build network systems and Virtual Network Functions (VNF) in heterogeneous deployment environments ? Explore various Python modules to program the Internet In Detail Python Network Programming Cookbook - Second Edition highlights the major aspects of network programming in Python, starting from writing simple networking clients to developing and deploying complex Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) systems. It creates the building blocks for many practical web and networking applications that rely on various networking protocols. It presents the power and beauty of Python to solve numerous real-world tasks in the area of network programming, network and system administration, network monitoring, and web-application development. In this edition, you will also be introduced to network modelling to build your own cloud network. You will learn about the concepts and fundamentals of SDN and then extend your network with Mininet. Next, you’ll find recipes on Authentication, Authorization, and Accounting (AAA) and open and proprietary SDN approaches and frameworks. You will also learn to configure the Linux Foundation networking ecosystem and deploy and automate your networks with Python in the cloud and the Internet scale. By the end of this book, you will be able to analyze your network security vulnerabilities using advanced network packet capture and analysis techniques. Style and approach This book follows a practical approach and covers major aspects of network programming in Python. It provides hands-on recipes combined with short and concise explanations on code snippets. This book will serve as a supplementary material to develop hands-on skills in any academic course on network programming. This book further elaborates network softwarization, including Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and orchestration. We learn to configure and deploy enterprise network platforms, develop applications on top of them with Python.

Apply Functional Programming techniques to C++ to build highly modular, testable, and reusable code About This Book ? Modularize your applications and make them highly reusable and testable ? Get familiar with complex concepts such as metaprogramming, concurrency, and immutability ? A highly practical guide to building functional code in C++ filled with lots of examples and real-world use cases Who This Book Is For This book is for C++ developers comfortable with OOP who are interested in learning how to apply the functional paradigm to create robust and testable apps. What You Will Learn ? Get to know the difference between imperative and functional approaches ? See the use of first-class functions and pure functions in a functional style ? Discover various techniques to apply immutable state to avoid side effects ? Design a recursive algorithm effectively ? Create faster programs using lazy evaluation ? Structure code using design patterns to make the design process easier ? Use concurrency techniques to develop responsive software ? Learn how to use the C++ Standard Template Library and metaprogramming in a functional way to improve code optimization In Detail Functional programming allows developers to divide programs into smaller, reusable components that ease the creation, testing, and maintenance of software as a whole. Combined with the power of C++, you can develop robust and scalable applications that fulfill modern day software requirements. This book will help you discover all the C++ 17 features that can be applied to build software in a functional way. The book is divided into three modules—the first introduces the fundamentals of functional programming and how it is supported by modern C++. The second module explains how to efficiently implement C++ features such as pure functions and immutable states to build robust applications. The last module describes how to achieve concurrency and apply design patterns to enhance your application’s performance. Here, you will also learn to optimize code using metaprogramming in a functional way. By the end of the book, you will be familiar with the functional approach of programming and will be able to use these techniques on a daily basis. Style and approach This book uses a module-based approach, where each module will cover important aspects of functional programming in C++ and will help you develop efficient and robust applications through gaining a practical understanding.

Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book ? Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more ? Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka ? An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn ? Understand the core concepts of Apache Storm and real-time processing ? Follow the steps to deploy multiple nodes of Storm Cluster ? Create Trident topologies to support various message-processing semantics ? Make your cluster sharing effective using Storm scheduling ? Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more ? Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.

Extract patterns and knowledge from your data in easy way using MATLAB About This Book ? Get your first steps into machine learning with the help of this easy-to-follow guide ? Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB ? Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn ? Learn the introductory concepts of machine learning. ? Discover different ways to transform data using SAS XPORT, import and export tools, ? Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. ? Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. ? Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. ? Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. ? Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book ? Process and analyze big data in a distributed and scalable way ? Write sophisticated Spark pipelines that incorporate elaborate extraction ? Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn ? Use Spark streams to cluster tweets online ? Run the PageRank algorithm to compute user influence ? Perform complex manipulation of DataFrames using Spark ? Define Spark pipelines to compose individual data transformations ? Utilize generated models for off-line/on-line prediction ? Transfer the learning from an ensemble to a simpler Neural Network ? Understand basic graph properties and important graph operations ? Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language ? Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.

Build consistent web apps with Redux by easily centralizing the state of your application. About This Book ? Write applications that behave consistently, run in different environments (client, server and native), and are easy to test ? Take your web apps to the next level by combining the power of Redux with other frameworks such as React and Angular ? Uncover the best practices and hidden features of Redux to build applications that are powerful, consistent, and maintainable Who This Book Is For This book targets developers who are already fluent in JavaScript but want to extend their web development skills to develop and maintain bigger applications. What You Will Learn ? Understand why and how Redux works ? Implement the basic elements of Redux ? Use Redux in combination with React/Angular to develop a web application ? Debug a Redux application ? Interface with external APIs with Redux ? Implement user authentication with Redux ? Write tests for all elements of a Redux application ? Implement simple and more advanced routing with Redux ? Learn about server-side rendering with Redux and React ? Create higher-order reducers for Redux ? Extend the Redux store via middleware In Detail The book starts with a short introduction to the principles and the ecosystem of Redux, then moves on to show how to implement the basic elements of Redux and put them together. Afterward, you are going to learn how to integrate Redux with other frameworks, such as React and Angular. Along the way, you are going to develop a blog application. To practice developing growing applications with Redux, we are going to start from nothing and keep adding features to our application throughout the book. You are going to learn how to integrate and use Redux DevTools to debug applications, and access external APIs with Redux. You are also going to get acquainted with writing tests for all elements of a Redux application. Furthermore, we are going to cover important concepts in web development, such as routing, user authentication, and communication with a backend server After explaining how to use Redux and how powerful its ecosystem can be, the book teaches you how to make your own abstractions on top of Redux, such as higher-order reducers and middleware. By the end of the book, you are going to be able to develop and maintain Redux applications with ease. In addition to learning about Redux, you are going be familiar with its ecosystem, and learn a lot about JavaScript itself, including best practices and patterns. Style and approach This practical guide will teach you how to develop a complex, data-intensive application leveraging the capabilities of the Redux framework.

A complete guide on using data structures and algorithms to write sophisticated C# code About This Book ? Master array, set and map with trees and graphs, among other fundamental data structures ? Delve into effective design and implementation techniques to meet your software requirements ? Explore illustrations to present data structures and algorithms, as well as their analysis in a clear, visual manner. Who This Book Is For This book is for developers who would like to learn the Data Structures and Algorithms in C#. Basic C# programming knowledge would be an added advantage. What You Will Learn ? How to use arrays and lists to get better results in complex scenarios ? Implement algorithms like the Tower of Hanoi on stacks of C# objects ? Build enhanced applications by using hashtables, dictionaries and sets ? Make a positive impact on efficiency of applications with tree traversal ? Effectively find the shortest path in the graph In Detail Data structures allow organizing data efficiently. They are critical to various problems and their suitable implementation can provide a complete solution that acts like reusable code. In this book, you will learn how to use various data structures while developing in the C# language as well as how to implement some of the most common algorithms used with such data structures. At the beginning, you will get to know arrays, lists, dictionaries, and sets together with real-world examples of your application. Then, you will learn how to create and use stacks and queues. In the following part of the book, the more complex data structures will be introduced, namely trees and graphs, together with some algorithms for searching the shortest path in a graph. We will also discuss how to organize the code in a manageable, consistent, and extendable way. By the end of the book,you will learn how to build components that are easy to understand, debug, and use in different applications. Style and approach Readers will be taken through all the indispensable data structures and algorithms so they can begin their coding journey in C#. At each step, the book will show how to implement these via examples while also discussing the attributes of each algorithm so readers are capable to make an informed choice.

Leverage the power of the Reinforcement Learning techniques to develop self-learning systems using Tensorflow About This Book ? Learn reinforcement learning concepts and their implementation using TensorFlow ? Discover different problem-solving methods for Reinforcement Learning ? Apply reinforcement learning for autonomous driving cars, robobrokers, and more Who This Book Is For If you want to get started with reinforcement learning using TensorFlow in the most practical way, this book will be a useful resource. The book assumes prior knowledge of machine learning and neural network programming concepts, as well as some understanding of the TensorFlow framework. No previous experience with Reinforcement Learning is required. What You Will Learn ? Implement state-of-the-art Reinforcement Learning algorithms from the basics ? Discover various techniques of Reinforcement Learning such as MDP, Q Learning and more ? Learn the applications of Reinforcement Learning in advertisement, image processing, and NLP ? Teach a Reinforcement Learning model to play a game using TensorFlow and the OpenAI gym ? Understand how Reinforcement Learning Applications are used in robotics In Detail Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence—from games, self-driving cars and robots to enterprise applications that range from datacenter energy saving (cooling data centers) to smart warehousing solutions. The book covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. The book also introduces readers to the concept of Reinforcement Learning, its advantages and why it’s gaining so much popularity. The book also discusses on MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP. By the end of this book, you will have a firm understanding of what reinforcement learning is and how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym. Style and approach An Easy-to-follow, step-by-step guide to help you get to grips with real-world applications of Reinforcement Learning with TensorFlow.