Over 80 recipes to teach you the power of vRealize Configuration Manager 5.8 to provide automated and continuous configuration management About This Book First book in the market that provides a broad configuration and compliance management solution for your enterprise. Champion the skills of the latest features of VMware vRealize Configuration Manager and implement it in your organization. A recipe based approach book that will enlighten you to configure VCM to collect and manage data from your virtual and physical environment. Who This Book Is For If you are a system administrator who is eager to provide better administration with VCM and are familiar with managing network users and resources along with performing system maintenance, then this book is for you. What You Will Learn Find out how to configure automated patching of your infrastructure for Windows as well Unix machines Maintain and upgrade your vRealize Configuration Manager Integrate with other VMware tools such as vCloud Director, vRealise Operations, vCenter, and vCloud Network and Security Understand what vRealize Configuration Manager is and what its capacities are Explore how vRealize Configuration Manager can be used for patching, compliance management, and software distribution Troubleshoot vRealize Configuration Manager with ease In Detail VMware vRealize Configuration Manager (VCM) helps you to automate IT operations, manage performance, and gain visibility across physical and virtual infrastructure. It is continuously being used by enterprises to audit the configurations of the VMware infrastructure as well as the Windows, Linux, and UNIX operating systems. This book is filled with practical recipes through which you will learn about the latest features of vRealize Configuration Manager 5.8.X, starting with installation of various tiers of VCM followed by configuration management across physical and virtual servers. Throughout this book, you will explore how VCM can perform tasks such as patch management, compliance assessment, and software package distribution along with Machine filters for new platforms such as RHEL 7 and Windows 10. This book will ease your troubles while upgrading from the existing VCM to the latest version by providing you with step-by-step instructions about the process of migration along with upgrade and maintenance support. This book will help you understand how to integrate vRealize Configuration with other applications along with schedule management and also guide you on how to handle security issues. After reading this book, you will have a clear understanding of how VCM fits in the overall picture of the data center design from a patching and compliance perspective. Style and approach This book takes a recipe-based approach that will provide you with an effective and a practical configuration management solution for your enterprise.

Master the art of getting the maximum out of your machine data using Splunk About This Book A practical and comprehensive guide to the advanced functions of Splunk,, including the new features of Splunk 6.3 Develop and manage your own Splunk apps for greater insight from your machine data Full coverage of high-level Splunk techniques including advanced searches, manipulations, and visualization Who This Book Is For This book is for Splunk developers looking to learn advanced strategies to deal with big data from an enterprise architectural perspective. It is expected that readers have a basic understanding and knowledge of using Splunk Enterprise. What You Will Learn Find out how to develop and manage apps in Splunk Work with important search commands to perform data analytics on uploaded data Create visualizations in Splunk Explore tweaking Splunk Integrate Splunk with any pre-existing application to perform data crunching efficiently and in real time Make your big data speak with analytics and visualizations using Splunk Use SDK and Enterprise integration with tools such as R and Tableau In Detail Master the power of Splunk and learn the advanced strategies to get the most out of your machine data with this practical advanced guide. Make sense of the hidden data of your organization – the insight of your servers, devices, logs, traffic and clouds. Advanced Splunk shows you how. Dive deep into Splunk to find the most efficient solution to your data problems. Create the robust Splunk solutions you need to make informed decisions in big data machine analytics. From visualizations to enterprise integration, this well-organized high level guide has everything you need for Splunk mastery. Start with a complete overview of all the new features and advantages of the latest version of Splunk and the Splunk Environment. Go hands on with uploading data, search commands for basic and advanced analytics, advanced visualization techniques, and dashboard customizing. Discover how to tweak Splunk to your needs, and get a complete on Enterprise Integration of Splunk with various analytics and visualization tools. Finally, discover how to set up and use all the new features of the latest version of Splunk. Style and approach This book follows a step by step approach. Every new concept is built on top of its previous chapter, and it is full of examples and practical scenarios to help the reader experiment as they read.

Master the art of making Docker more extensible, composable, and modular by leveraging plugins and other supporting tools About This Book Get the first book on the market that shows you how to extend the capabilities of Docker using plugins and third-party tools Master the skills of creating various plugins and integrating great tools in order to enhance the functionalities of Docker A practical and learning guide that ensures your investment in Docker becomes more valuable Who This Book Is For This book is for developers and sys admins who are well versed Docker and have knowledge on basic programming languages. If you can’t wait to extend Docker and customize it to meet your requirements, this is the book for you! What You Will Learn Find out about Docker plugins and the problems they solve Gain insights into creating your own plugin Use Docker tools to extend the basic functionality of the core Docker engine Get to grips with the installation and configuration of third-party tools available to use with Docker plugins Install, configure, and use a scheduling service to manage the containers in your environment Enhance your day-to-day Docker usage through security, troubleshooting, and best practices In Detail With Docker, it is possible to get a lot of apps running on the same old servers, making it very easy to package and ship programs. The ability to extend Docker using plugins and load third-party plugins is incredible, and organizations can massively benefit from it. In this book, you will read about what first and third party tools are available to extend the functionality of your existing Docker installation and how to approach your next Docker infrastructure deployment. We will show you how to work with Docker plugins, install it, and cover its lifecycle. We also cover network and volume plugins, and you will find out how to build your own plugin. You’ll discover how to integrate it with Puppet, Ansible, Jenkins, Flocker, Rancher, Packer, and more with third-party plugins. Then, you’ll see how to use Schedulers such as Kubernetes and Amazon ECS. Finally, we’ll delve into security, troubleshooting, and best practices when extending Docker. By the end of this book, you will learn how to extend Docker and customize it based on your business requirements with the help of various tools and plugins. Style and approach An easy to follow guide with plenty of hands-on practical examples which can be executed both on your local machine or externally hosted services.

Create fast, scalable, and high performance applications with C#, ASP.NET Core 1.0, and MVC 6 About This Book Learn the importance of measuring, profiling, and locating the most impactful problems Discover the common areas you might encounter performance problems and areas you don’t need to worry about Understand the differences between development workstations and production infrastructure and how these can amplify problems Design workflows that run asynchronously and are resilient to transient performance issues Who This Book Is For This book is for ASP.NET and C# developers who have experience with the MVC framework for web application development and are looking to deploy applications that will perform well in live production environments. These could be virtual machines or hosted by a cloud service provider such as AWS or Azure. What You Will Learn Why performance matters and when it should be considered Use different tools to measure performance Spot common performance issues, their root causes, and how to easily mitigate them Improve performance at the network level and I/O level, and how to optimize the application as a whole Work with caching and message queuing tools, including patterns and strategies Discover the dark side of performance improvement and find out how to manage complexity Monitor performance as part of continuous integration and regression testing Assess and solve performance issues with other advanced technologies In Detail ASP.NET Core is the new, open source, and cross-platform, web-application framework from Microsoft. It's a stripped down version of ASP.NET that's lightweight and fast. This book will show you how to make your web apps deliver high performance when using it. We'll address many performance improvement techniques from both a general web standpoint and from a C#, ASP.NET Core, and .NET Core perspective. This includes delving into the latest frameworks and demonstrating software design patterns that improve performance. We will highlight common performance pitfalls, which can often occur unnoticed on developer workstations, along with strategies to detect and resolve these issues early. By understanding and addressing challenges upfront, you can avoid nasty surprises when it comes to deployment time. We will introduce performance improvements along with the trade-offs that they entail. We will strike a balance between premature optimization and inefficient code by taking a scientific- and evidence-based approach. We'll remain pragmatic by focusing on the big problems. By reading this book, you'll learn what problems can occur when web applications are deployed at scale and know how to avoid or mitigate these issues. You'll gain experience of how to write high-performance applications without having to learn about issues the hard way. You'll see what's new in ASP.NET Core, why it's been rebuilt from the ground up, and what this means for performance. You will understand how you can now develop on and deploy to Windows, Mac OS X, and Linux using cross-platform tools, such as Visual Studio Code. Style and approach Starting with a drill down into the nuts and bolts of various performance parameters, you will get an understanding of the ASP.NET MVC 6 framework with the help of rich code-based examples that will equip you to build highly scalable and optimized applications.

Build scalable microservices with Spring, Docker, and Mesos About This Book Learn how to efficiently build and implement microservices in Spring, and how to use Docker and Mesos to push the boundaries of what you thought possible Examine a number of real-world use cases and hands-on code examples. Distribute your microservices in a completely new way Who This Book Is For If you are a Spring developers and want to build cloud-ready, internet-scale applications to meet modern business demands, then this book is for you Developers will understand how to build simple Restful services and organically grow them to truly enterprise grade microservices ecosystems. What You Will Learn Get to know the microservices development lifecycle process See how to implement microservices governance Familiarize yourself with the microservices architecture and its benefits Use Spring Boot to develop microservices Find out how to avoid common pitfalls when developing microservices Be introduced to end-to-end microservices written in Spring Framework and Spring Boot In Detail The Spring Framework is an application framework and inversion of the control container for the Java platform. The framework's core features can be used by any Java application, but there are extensions to build web applications on top of the Java EE platform. This book will help you implement the microservice architecture in Spring Framework, Spring Boot, and Spring Cloud. Written to the latest specifications of Spring, you'll be able to build modern, Internet-scale Java applications in no time. We would start off with the guidelines to implement responsive microservices at scale. We will then deep dive into Spring Boot, Spring Cloud, Docker, Mesos, and Marathon. Next you will understand how Spring Boot is used to deploy autonomous services, server-less by removing the need to have a heavy-weight application server. Later you will learn how to go further by deploying your microservices to Docker and manage it with Mesos. By the end of the book, you'll will gain more clarity on how to implement microservices using Spring Framework and use them in Internet-scale deployments through real-world examples. Style and approach The book follows a step by step approach on how to develop microservices using Spring Framework, Spring Boot, and a set of Spring Cloud components that will help you scale your applications.

Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop About This Book This is a primer on functional-programming-style techniques to help you efficiently process and analyze all of your data Get acquainted with the best and newest tools available such as Scala, Spark, Parquet and MLlib for machine learning Learn the best practices to incorporate new Big Data machine learning in your data-driven enterprise to gain future scalability and maintainability Who This Book Is For Mastering Scala Machine Learning is intended for enthusiasts who want to plunge into the new pool of emerging techniques for machine learning. Some familiarity with standard statistical techniques is required. What You Will Learn Sharpen your functional programming skills in Scala using REPL Apply standard and advanced machine learning techniques using Scala Get acquainted with Big Data technologies and grasp why we need a functional approach to Big Data Discover new data structures, algorithms, approaches, and habits that will allow you to work effectively with large amounts of data Understand the principles of supervised and unsupervised learning in machine learning Work with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquet Construct reliable and robust data pipelines and manage data in a data-driven enterprise Implement scalable model monitoring and alerts with Scala In Detail Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level and help you impart that knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees. Most of the data that we produce today is unstructured and raw, and you will learn to tackle this type of data with advanced topics such as regression, classification, integration, and working with graph algorithms. Finally, you will discover at how to use Scala to perform complex concept analysis, to monitor model performance, and to build a model repository. By the end of this book, you will have gained expertise in performing Scala machine learning and will be able to build complex machine learning projects using Scala. Style and approach This hands-on guide dives straight into implementing Scala for machine learning without delving much into mathematical proofs or validations. There are ample code examples and tricks that will help you sail through using the standard techniques and libraries. This book provides practical examples from the field on how to correctly tackle data analysis problems, particularly for modern Big Data datasets.

Become an expert at using Python for advanced statistical analysis of data using real-world examples About This Book Clean, format, and explore data using graphical and numerical summaries Leverage the IPython environment to efficiently analyze data with Python Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For If you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you. Familiarity with the basics of applying Python libraries to data sets is assumed. What You Will Learn Read, sort, and map various data into Python and Pandas Recognise patterns so you can understand and explore data Use statistical models to discover patterns in data Review classical statistical inference using Python, Pandas, and SciPy Detect similarities and differences in data with clustering Clean your data to make it useful Work in Jupyter Notebook to produce publication ready figures to be included in reports In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your dataWell, look no further, this is the book you want! Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You’ll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. You’ll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you’ll move on to review statistical inference using Python, Pandas, and SciPy. After that, we’ll focus on performing regression using computational tools and you’ll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you’ll discover how to use Python’s tools for supervised machine learning. Style and approach This book takes a step-by-step approach to reading, processing, and analyzing data in Python using various methods and tools. Rich in examples, each topic connects to real-world examples and retrieves data directly online where possible. With this book, you are given the knowledge and tools to explore any data on your own, encouraging a curiosity befitting all data scientists.

Bring life to your robot using ROS robotic applications About This Book .This book will help you boost your knowledge of ROS and give you advanced practical experience you can apply to your ROS robot platforms.This is the only book that offers you step-by-step instructions to solidify your ROS understanding and gain experience using ROS tools.From eminent authors, this book offers you a plethora of fun-filled examples to make your own quadcopter, turtlebot, and two-armed robots Who This Book Is For If you are a robotics developer, whether a hobbyist, researchers or professional, and are interested in learning about ROS through a hands-on approach, then this book is for you. You are encouraged to have a working knowledge of GNU/Linux systems and Python. What You Will Learn .Get to know the fundamentals of ROS and apply its concepts to real robot examples.Control a mobile robot to navigate autonomously in an environment.Model your robot designs using URDF and Xacro, and operate them in a ROS Gazebo simulation.Control a 7 degree-of-freedom robot arm for visual servoing.Fly a quadcopter to autonomous waypoints.Gain working knowledge of ROS tools such as Gazebo, rviz, rqt, and Move-It.Control robots with mobile devices and controller boards In Detail The visionaries who created ROS developed a framework for robotics centered on the commonality of robotic systems and exploited this commonality in ROS to expedite the development of future robotic systems. From the fundamental concepts to advanced practical experience, this book will provide you with an incremental knowledge of the ROS framework, the backbone of the robotics evolution. ROS standardizes many layers of robotics functionality from low-level device drivers to process control to message passing to software package management. This book provides step-by-step examples of mobile, armed, and flying robots, describing the ROS implementation as the basic model for other robots of these types. By controlling these robots, whether in simulation or in reality, you will use ROS to drive, move, and fly robots using ROS control. Style and approach This is an easy-to-follow guide with hands-on examples of ROS robots, both real and in simulation.

Harness actionable insights from your data with computational statistics and simulations using R About This Book Learn five different simulation techniques (Monte Carlo, Discrete Event Simulation, System Dynamics, Agent-Based Modeling, and Resampling) in-depth using real-world case studies A unique book that teaches you the essential and fundamental concepts in statistical modeling and simulation Who This Book Is For This book is for users who are familiar with computational methods. If you want to learn about the advanced features of R, including the computer-intense Monte-Carlo methods as well as computational tools for statistical simulation, then this book is for you. Good knowledge of R programming is assumed/required. What You Will Learn The book aims to explore advanced R features to simulate data to extract insights from your data. Get to know the advanced features of R including high-performance computing and advanced data manipulation See random number simulation used to simulate distributions, data sets, and populations Simulate close-to-reality populations as the basis for agent-based micro-, model- and design-based simulations Applications to design statistical solutions with R for solving scientific and real world problems Comprehensive coverage of several R statistical packages like boot, simPop, VIM, data.table, dplyr, parallel, StatDA, simecol, simecolModels, deSolve and many more. In Detail Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. The book will provide a computational and methodological framework for statistical simulation to the users. Through this book, you will get in grips with the software environment R. After getting to know the background of popular methods in the area of computational statistics, you will see some applications in R to better understand the methods as well as gaining experience of working with real-world data and real-world problems. This book helps uncover the large-scale patterns in complex systems where interdependencies and variation are critical. An effective simulation is driven by data generating processes that accurately reflect real physical populations. You will learn how to plan and structure a simulation project to aid in the decision-making process as well as the presentation of results. By the end of this book, you reader will get in touch with the software environment R. After getting background on popular methods in the area, you will see applications in R to better understand the methods as well as to gain experience when working on real-world data and real-world problems. Style and approach This book takes a practical, hands-on approach to explain the statistical computing methods, gives advice on the usage of these methods, and provides computational tools to help you solve common problems in statistical simulation and computer-intense methods.

Arm yourself to make the most of the versatile, powerful Ubuntu Server with over 100 hands-on recipes About This Book Master the skills to setup secure and scalable web services with popular tools like Apache, Nginx, MySQL and HAProxy Set up your own cloud with Open Stack and quickly deploy applications with Docker or LXD Packed with clear, step-by-step recipes to let you protect you valuable data with your own chat servers, code hosting and collaboration tools. Who This Book Is For Ubuntu Server Cookbook is for system administrators or software developers with a basic understanding of the Linux operating system who want to set up their own servers. You are not required to have in-depth knowledge or hands-on experience with Ubuntu, but you should know the basics commands for directory navigation, file management, and the file editing tool. An understanding of computer networks is advisable What You Will Learn Set up high performance, scalable, and fault-tolerant back ends with web and database servers Facilitate team communication with a real-time chat service and collaboration tools Quickly deploy your applications to their own containers and scale your infrastructure as and when needed Find out how to set up your own cloud infrastructure for your internal use or rent it to the public Ensure quick and easy access for your users while also securing your infrastructure from intruders Set up a high performance private network with a personal VPN server and centralized authentication system Swiftly start a content streaming service Set up network storage for private data and source code and say good bye to costly and unreliable cloud services In Detail Ubuntu is one of the most secure operating systems and defines the highest level of security as compared other operating system. Ubuntu server is a popular Linux distribution and the first choice when deploying a Linux server. It can be used with a $35 Raspberry Pi to top-notch, thousand-dollar-per-month cloud hardware. Built with lists that there are 4 million + websites built using Ubuntu. With its easy-to-use package management tools and availability of well-known packages, we can quickly set up our own services such as web servers and database servers using Ubuntu. This book will help you develop the skills required to set up high performance and secure services with open source tools. Starting from user management and an in-depth look at networking, we then move on to cover the installation and management of web servers and database servers, as well as load balancing various services. You will quickly learn to set up your own cloud and minimize costs and efforts with application containers. Next, you will get to grips with setting up a secure real-time communication system. Finally, we’ll explore source code hosting and various collaboration tools. By the end of this book, you will be able to make the most of Ubuntu’s advanced functionalities. Style and approach This easy-to-follow guide contains a series of step-by-step recipes ranging from simple to complex. Each topic will start with basic introduction to each technology followed by a detailed step-by-step installation guide and then a detailed explanation of the approach taken during installation and the various advanced options available.

Design and implement real-world web-based applications using the Spring Framework 4.x specification based on technical documentation About This Book . Learn all the details of implementing Spring 4.x MVC applications from basic core platform construction to advanced integration implementations. Gain a complete reference guide to implementing the controllers, models, views, view resolvers, and other service-related components to solve various real-world problems. Discover the possible optimal solutions for developers and experts to build enterprise and personal web-based applications. Create a Spring MVC application that has a validation process and exception handling with the HTTP status codes Who This Book Is For This book is for competent Spring developers who wish to understand how to develop complex yet flexible applications with Spring MVC. You must have a good knowledge of JAVA programming and be familiar with the basics of Spring. What You Will Learn . Set up and configure the Spring 4.x MVC platform from ground level up using the basic Spring Framework 4.x APIs. Study requirements and manage solutions on file uploading transactions in Spring 4.x applications Configure, , and test Spring integration to the Hibernate, MyBatis, and JPA frameworks for database transactions. Properly implement exception handlers and audit trails in Spring MVC applications. Generate reports using JFreeChart, Google Charts, JasperReports, DynamicReports, FreeMarker, Velocity, and Spring’s API known as ContentNegotiatingViewResolver. Configure security and flexibility by adding Captcha, Spring Security, Spring Flow, Spring Portlets, JTA to improve data management performance. Implement web services using Spring’s RESTful implementation and other service-oriented integration plugins. Design and implement a Spring 4.x application using AngularJS, ExtJs, Twitter Bootstrap, and Spring Mobile for responsive web design In Detail Spring MVC is the ideal tool to build modern web applications on the server side. With the arrival of Spring Boot, developers can really focus on the code and deliver great value, leveraging the rich Spring ecosystem with minimal configuration. Spring makes it simple to create RESTful applications, interact with social services, communicate with modern databases, secure your system, and make your code modular and easy to test. It is also easy to deploy the result on different cloud providers. This book starts all the necessary topics in starting a Spring MVC-based application. Moving ahead it explains how to design model objects to handle file objects. save files into a data store and how Spring MVC behaves when an application deals with uploading and downloading files. Further it highlights form transactions and the user of Validation Framework as the tool in validating data input. It shows how to create a customer feedback system which does not require a username or password to log in. It will show you the soft side of Spring MVC where layout and presentation are given importance. Later it will discuss how to use Spring Web Flow on top of Spring MVC to create better web applications. Moving ahead, it will teach you how create an Invoice Module that receives and transport data using Web Services By the end of the book you will be able to create efficient and flexible real-time web applications using all the frameworks in Spring MVC. Style and approach This book is a compendium of technical specification documents that will guide you through building an application using Spring 4.x MVC. Each chapter starts with a high-level wireframe design of the software followed by how to set up and configure different libraries and tools.

Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps About This Book Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books Who This Book Is For This book teaches Python data analysis at an intermediate level with the goal of transforming you from journeyman to master. Basic Python and data analysis skills and affinity are assumed. What You Will Learn Set up reproducible data analysis Clean and transform data Apply advanced statistical analysis Create attractive data visualizations Web scrape and work with databases, Hadoop, and Spark Analyze images and time series data Mine text and analyze social networks Use machine learning and evaluate the results Take advantage of parallelism and concurrency In Detail Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You’ll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration *s for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios. Style and Approach The book is written in “cookbook” style striving for high realism in data analysis. Through the recipe-based format, you can read each recipe separately as required and immediately apply the knowledge gained.

Discover over 125 solution-based recipes to help you build applications for smartphones, tablets, and desktops About This Book Learn to build applications for Windows 10, the latest Windows version Develop your applications to be compatible with smartphones, tablets, and desktops This guide is packed with recipes covering major solutions to day-to-day problems faced by Windows programmers Who This Book Is For The book is dedicated to programmers with various experience of developing applications for Windows-based smartphones, tablets, and desktops—even beginners can find suitable content. What You Will Learn Start developing universal applications for Windows 10 Design user interface in the XAML language Use the MVVM design pattern with data binding Store data in files and in a database Use multimedia content and animations Capture data from built-in sensors Handle various Internet-based scenarios Test the application and submit it to the Windows Store In Detail Need to ensure you can always create the best Windows apps regardless of platformWhat you need are solutions to the biggest issues you can face, so you can always ensure you’re making the right choices and creating the best apps you can. The book starts with recipes that will help you set up the integrated development environment before you go ahead and design the user interface. You will learn how to use the MVVM design pattern together with data binding, as well as how to work with data in different file formats. Moving on, you will explore techniques to add animations and graphics to your application, and enable your solution to work with multimedia content. You will also see how to use sensors, such as an accelerometer and a compass, as well as obtain the current GPS location. You will make your application ready to work with Internet-based scenarios, such as composing e-mails or downloading files, before finally testing the project and submitting it to the Windows Store. By the end of the book, you will have a market-ready application compatible across different Windows devices, including smartphones, tablets, and desktops. Style and approach This quick-start book takes a cookbook format with recipes covering more than 125 solutions to help you create and build applications for Windows 10. The examples presented in the book use the free integrated development environment. A supporting set of codes that present solutions to problems described in particular chapters is available as well.

Combine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles! About This Book This highly practical guide shows you how to use the best of the big data technologies to solve your response-critical problems Learn the art of making cheap-yet-effective big data architecture without using complex Greek-letter architectures Use this easy-to-follow guide to build fast data processing systems for your organization Who This Book Is For If you are a developer, data architect, or a data scientist looking for information on how to integrate the Big Data stack architecture and how to choose the correct technology in every layer, this book is what you are looking for. What You Will Learn Design and implement a fast data Pipeline architecture Think and solve programming challenges in a functional way with Scala Learn to use Akka, the actors model implementation for the JVM Make on memory processing and data analysis with Spark to solve modern business demands Build a powerful and effective cluster infrastructure with Mesos and Docker Manage and consume unstructured and No-SQL data sources with Cassandra Consume and produce messages in a massive way with Kafka In Detail SMACK is an open source full stack for big data architecture. It is a combination of Spark, Mesos, Akka, Cassandra, and Kafka. This stack is the newest technique developers have begun to use to tackle critical real-time analytics for big data. This highly practical guide will teach you how to integrate these technologies to create a highly efficient data analysis system for fast data processing. We’ll start off with an introduction to SMACK and show you when to use it. First you’ll get to grips with functional thinking and problem solving using Scala. Next you’ll come to understand the Akka architecture. Then you’ll get to know how to improve the data structure architecture and optimize resources using Apache Spark. Moving forward, you’ll learn how to perform linear scalability in databases with Apache Cassandra. You’ll grasp the high throughput distributed messaging systems using Apache Kafka. We’ll show you how to build a cheap but effective cluster infrastructure with Apache Mesos. Finally, you will deep dive into the different aspect of SMACK using a few case studies. By the end of the book, you will be able to integrate all the components of the SMACK stack and use them together to achieve highly effective and fast data processing. Style and approach With the help of various industry examples, you will learn about the full stack of big data architecture, taking the important aspects in every technology. You will learn how to integrate the technologies to build effective systems rather than getting incomplete information on single technologies. You will learn how various open source technologies can be used to build cheap and fast data processing systems with the help of various industry examples

Create beautiful data visualizations and interactive dashboards with Tableau About This Book Delve into the features and functionalities of Tableau from the ground up with this step-by-step guide that has over 50 "follow-me" recipes Build rich visualizations to effectively highlight the underlying trends and patterns in your data Build beautiful interactive dashboards and storyboards to stitch your visualizations together and tell a story Who This Book Is For This book is for anyone who wishes to use Tableau. It will be of use to both beginners who want to learn Tableau from scratch and to more seasoned users who simply want a quick reference guide. This book is a ready reckoner guide for you. The book will be such that both new & existing Tableau users who don’t know, or can’t recall how to perform different Tableau tasks can use the book and be benefited from it. What You Will Learn Get to grips with the Tableau workspace and terminologies and understand what data sources you can connect Learn to create basic charts like bar chart, stacked bar, pie chart, line chart, area chart, tree map & word cloud Go even further with more advanced visualizations such as scatter plot, box & whiskers plot, dual axis, bullet chart, Histograms, Maps, etc Use pre-defined calculation and change its scope and direction to affect outcome Learn to define Parameters and call them into parametric calculations that provide outcomes based on user inputs Build Dashboards and use Actions to link multiple sheets on the dashboard Connect to multiple data sources using Data Blending, Multiple Table Join within the same data source as well as across data sources, Custom SQL and learn to work with data Extracts Compute statistical trends, build forecasting models and use Reference lines for benchmarking In Detail Data is everywhere and everything is data! Visualization of data allows us to bring out the underlying trends and patterns inherent in the data and gain insights that enable faster and smarter decision making. Tableau is one of the fastest growing and industry leading Business Intelligence platforms that empowers business users to easily visualize their data and discover insights at the speed of thought. Tableau is a self-service BI platform designed to make data visualization and analysis as intuitive as possible. Creating visualizations with simple drag-and-drop, you can be up and running on Tableau in no time. Starting from the fundamentals such as getting familiarized with Tableau Desktop, connecting to common data sources and building standard charts; you will walk through the nitty gritty of Tableau such as creating dynamic analytics with parameters, blended data sources, and advanced calculations. You will also learn to group members into higher levels, sort the data in a specific order & filter out the unnecessary information. You will then create calculations in Tableau & understand the flexibility & power they have and go on to building story-boards and share your insights with others. Whether you are just getting started or whether you need a quick reference on a "how-to" question, This book is the perfect companion for you Style and approach This cookbook takes a step-by-step approach and the text systematically evolves to cover more involved functionalities. Every recipe includes illustrative screenshots which provide a detailed visual resource for each step.

Find out everything you need to know to build powerful robots with the most up-to-date ROS About This Book This comprehensive, yet easy-to-follow guide will help you find your way through the ROS framework Successfully design and simulate your 3D robot model and use powerful robotics algorithms and tools to program and set up your robots with an unparalleled experience by using the exciting new features from Robot Kinetic Use the latest version of gazebo simulator, OpenCV 3.0, and C++11 standard for your own algorithms Who This Book Is For This book is suitable for an ROS beginner as well as an experienced ROS roboticist or ROS user or developer who is curious to learn ROS Kinetic and its features to make an autonomous Robot. The book is also suitable for those who want to integrate sensors and embedded systems with other software and tools using ROS as a framework. What You Will Learn Understand the concepts of ROS, the command-line tools, visualization GUIs, and how to debug ROS Connect robot sensors and actuators to ROS Obtain and analyze data from cameras and 3D sensors Use Gazebo for robot/sensor and environment simulation Design a robot and see how to make it map the environment, navigate autonomously, and manipulate objects in the environment using MoveIt! Add vision capabilities to the robot using OpenCV 3.0 Add 3D perception capabilities to the robot using the latest version of PCL In Detail Building and programming a robot can be cumbersome and time-consuming, but not when you have the right collection of tools, libraries, and more importantly expert collaboration. ROS enables collaborative software development and offers an unmatched simulated environment that simplifies the entire robot building process. This book is packed with hands-on examples that will help you program your robot and give you complete solutions using open source ROS libraries and tools. It also shows you how to use virtual machines and Docker containers to simplify the installation of Ubuntu and the ROS framework, so you can start working in an isolated and control environment without changing your regular computer setup. It starts with the installation and basic concepts, then continues with more complex modules available in ROS such as sensors and actuators integration (drivers), navigation and mapping (so you can create an autonomous mobile robot), manipulation, Computer Vision, perception in 3D with PCL, and more. By the end of the book, you’ll be able to leverage all the ROS Kinetic features to build a fully fledged robot for all your needs. Style and approach This book is packed with hands-on examples that will help you program your robot and give you complete solutions using ROS open source libraries and tools. All the robotics concepts and modules are explained and multiple examples are provided so that you can understand them easily.

C++ has come a long way and is now adopted in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not to forget its importance in game programming. Despite its strengths in these areas, beginners usually tend to shy away from learning the language because of its steep learning curve. The main mission of this book is to make you familiar and comfortable with C++. You will finish the book not only being able to write your own code, but more importantly, you will be able to read other projects. It is only by being able to read others' code that you will progress from a beginner to an advanced programmer. This book is the first step in that progression. The first task is to familiarize you with the structure of C++ projects so you will know how to start reading a project. Next, you will be able to identify the main structures in the language, functions, and classes, and feel confident being able to identify the execution flow through the code. You will then become aware of the facilities of the standard library and be able to determine whether you need to write a routine yourself, or use an existing routine in the standard library. Throughout the book, there is a big emphasis on memory and pointers. You will understand memory usage, allocation, and

C# has recently been open-sourced and C# 7 comes with a host of new features for building powerful, cross-platform applications. This book will be your solution to some common programming problems that you come across with C# and will also help you get started with .NET Core 1.1. Through a recipe-based approach, this book will help you overcome common programming challenges and get your applications ready to face the modern world. We start by running you through new features in C# 7, such as tuples, pattern matching, and so on, giving you hands-on experience with them. Moving forward, you will work with generics and the OOP features in C#. You will then move on to more advanced topics, such as reactive extensions, Regex, code analyzers, and asynchronous programming. This book will also cover new, cross-platform .NET Core 1.1 features and teach you how to utilize .NET Core on macOS. Then, we will explore microservices as well as serverless computing and how these benefit modern developers. Finally, you will learn what you can do with Visual Studio 2017 to put mobile application development across multiple platforms within the reach of any developer. What you will learn ?Writing better and less code to achieve the same result as in previous versions of C# ?Working with analyzers in Visual Studio ?Working with files, streams, and serialization ?Writing high-performant code

Cisco Unified Computer System (UCS) is a powerful solution for modern data centers and is responsible for increasing efficiency and reducing costs. This hands-on guide will take you through deployment in Cisco UCS. Using real-world examples of configuring and deploying Cisco UCS components, we'll prepare you for the practical deployments of Cisco UCS data center solutions. If you want to develop and enhance your hands-on skills with Cisco UCS solutions, this book is certainly for you. We start by showing you the Cisco UCS equipment options, then introduce Cisco UCS Emulator so you can learn and practice deploying Cisco UCS components. We'll also introduce you to all the areas of UCS solutions through practical configuration examples. Moving on, you'll explore the Cisco UCS Manager, which is the centralized management interface for Cisco UCS. Once you get to know UCS Manager, you'll dive deeper into configuring LAN, SAN, identity pools, resource pools, and service profiles for the servers. You'll also get hands-on with administration topics including backup, restore, user's roles, and high availability cluster configuration. Finally, you will learn about virtualized networking, third-party integration tools, and testing failure scenarios. By the end of this book, you'll know everything you need to know to rapidly grow Cisco UCS deployments in the real world. What you will learn ?Set up your Lab using Cisco UCS Emulator ?Configure Cisco UCS, LAN, and SAN connectivity ?Create and manage Service profiles ?Perform various tasks using UCS ?Back up and restore Cisco UCS configuration ?Test various Cisco UCS scenarios

Build Machine Learning models with a sound statistical understanding. About This Book ? Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. ? Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. ? Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn ? Understand the Statistical and Machine Learning fundamentals necessary to build models ? Understand the major differences and parallels between the statistical way and the Machine Learning way to solve problems ? Learn how to prepare data and feed models by using the appropriate Machine Learning algorithms from the more-than-adequate R and Python packages ? Analyze the results and tune the model appropriately to your own predictive goals ? Understand the concepts of required statistics for Machine Learning ? Introduce yourself to necessary fundamentals required for building supervised & unsupervised deep learning models ? Learn reinforcement learning and its application in the field of artificial intelligence domain In Detail Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more. By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem. Style and approach This practical, step-by-step guide will give you an understanding of the Statistical and Machine Learning fundamentals you'll need to build models.

Advanced analytics on your Big Data with latest Apache Spark 2.x About This Book ? An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. ? Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark. ? Master the art of real-time processing with the help of Apache Spark 2.x Who This Book Is For If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected. What You Will Learn ? Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J ? Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming ? Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames ? Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud ? Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames ? Learn how specific parameter settings affect overall performance of an Apache Spark cluster ? Leverage Scala, R and python for your data science projects In Detail Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark’s functionality and implement your data flows and machine/deep learning programs on top of the platform. The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark 2.x. You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as interactive querying of live data and unifying DataFrames and Datasets. You will also learn about the updates on the APIs and how DataFrames and Datasets affect SQL, machine learning, graph processing, and streaming. You will learn to use Spark as a big data operating system, understand how to implement advanced analytics on the new APIs, and explore how easy it is to use Spark in day-to-day tasks. Style and approach This book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples.