Learn how to use RxClojure to deal with stateful computations Key Features * Leverage the features of Functional Reactive Programming using Clojure * Create dataflow-based systems that are the building blocks of Reactive Programming * Use different Functional Reactive Programming frameworks, techniques, and patterns to solve real-world problems Book Description Reactive Programming is central to many concurrent systems, and can help make the process of developing highly concurrent, event-driven, and asynchronous applications simpler and less error-prone. This book will allow you to explore Reactive Programming in Clojure 1.9 and help you get to grips with some of its new features such as transducers, reader conditionals, additional string functions, direct linking, and socket servers. Hands-On Reactive Programming with Clojure starts by introducing you to Functional Reactive Programming (FRP) and its formulations, as well as showing you how it inspired Compositional Event Systems (CES). It then guides you in understanding Reactive Programming as well as learning how to develop your ability to work with time-varying values thanks to examples of reactive applications implemented in different frameworks. You'll also gain insight into some interesting Reactive design patterns such as the simple component, circuit breaker, request-response, and multiple-master replication. Finally, the book introduces microservices-based architecture in Clojure and closes with examples of unit testing frameworks. By the end of the book, you will have gained all the knowledge you need to create applications using different Reactive Programming approaches. What you will learn * Understand how to think in terms of time-varying values and event streams * Create, compose, and transform observable sequences using Reactive extensions * Build a CES framework from scratch using core.async as its foundation * Develop a simple ClojureScript game using Reagi * Integrate Om and RxJS in a web application * Implement a reactive API in Amazon Web Services (AWS) * Discover helpful approaches to backpressure and error handling * Get to grips with futures and their applications Who this book is for If you’re interested in using Reactive Programming to build asynchronous and concurrent applications, this is the book for you. Basic knowledge of Clojure programming is necessary to understand the concepts covered in this book.

Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features * Exploit the power of Python to explore the world of data mining and data analytics * Discover machine learning algorithms to solve complex challenges faced by data scientists today * Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you’re interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You’ll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you’ll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you’ll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn * Understand the important concepts in machine learning and data science * Use Python to explore the world of data mining and analytics * Scale up model training using varied data complexities with Apache Spark * Delve deep into text and NLP using Python libraries such NLTK and gensim * Select and build an ML model and evaluate and optimize its performance * Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you’re a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial although not necessary.

Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features * Learn and implement machine learning algorithms in a variety of real-life scenarios * Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques * Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn * Use predictive modeling and apply it to real-world problems * Explore data visualization techniques to interact with your data * Learn how to build a recommendation engine * Understand how to interact with text data and build models to analyze it * Work with speech data and recognize spoken words using Hidden Markov Models * Get well versed with reinforcement learning, automated ML, and transfer learning * Work with image data and build systems for image recognition and biometric face recognition * Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key Features * Build state-of-the-art algorithms that can solve your business' problems * Learn how to find hidden patterns in your data * Revise key concepts with hands-on exercises using real-world datasets Book Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learn * Implement clustering methods such as k-means, agglomerative, and divisive * Write code in R to analyze market segmentation and consumer behavior * Estimate distribution and probabilities of different outcomes * Implement dimension reduction using principal component analysis * Apply anomaly detection methods to identify fraud * Design algorithms with R and learn how to edit or improve code Who this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.

Learn to distribute network traffic, optimize application delivery, and defend network-level threats. Key Features * Quickly get up and running with Azure networking solutions * Level-up your cloud networking skills by planning, implementing, configuring, and securing your infrastructure network with Azure * Leverage Azure networking services to provide applications highly available and fault tolerant environment Book Description Microsoft provides organizations with an effective way of managing their network with Azure's networking services. No matter the size of your organization, Azure provides a way to highly reliable performance and secure connectivity with its networking services. The book starts with an introduction to the Azure networking like creating Azure virtual networks, designing address spaces and subnets. Then you will learn to create and manage network security groups, application security groups, and IP addresses in Azure. Gradually, we move on to various aspects like S2S, P2S, and Vnet2Vnet connections, DNS and routing, load balancers and traffic manager. This book will cover every aspect and function required to deliver practical recipes to help readers learn from basic cloud networking practices to planning, implementing, and securing their infrastructure network with Azure. Readers will not only be able to upscale their current environment but will also learn to monitor, diagnose, and ensure secure connectivity. After learning to deliver a robust environment readers will also gain meaningful insights from recipes on best practices. By the end of this book, readers will gain hands-on experience in providing cost-effective solutions that benefit organizations. What you will learn * Learn to create Azure networking services * Understand how to create and work on hybrid connections * Configure and manage Azure network services * Learn ways to design high availability network solutions in Azure * Discover how to monitor and troubleshoot Azure network resources * Learn different methods of connecting local networks to Azure virtual networks Who this book is for This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on the Azure cloud. Some prior understanding of Microsoft Azure will be a plus point.

Understand the constructs of the Python programming language and use them to build data science projects Key Features * Learn the basics of developing applications with Python and deploy your first data application * Take your first steps in Python programming by understanding and using data structures, variables, and loops * Delve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in Python Book Description Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards. What you will learn * Code in Python using Jupyter and VS Code * Explore the basics of coding – loops, variables, functions, and classes * Deploy continuous integration with Git, Bash, and DVC * Get to grips with Pandas, NumPy, and scikit-learn * Perform data visualization with Matplotlib, Altair, and Datashader * Create a package out of your code using poetry and test it with PyTest * Make your machine learning model accessible to anyone with the web API Who this book is for If you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.

Explore the blockchain-based decentralized platform and understand how Ethereum works with Dapps examples Key Features * Explore the Ethereum ecosystem and understand the latest research on the platform * Build decentralized apps (Dapps) using smart contracts and Ethereum with the help of practical examples * Learn to make your decentralized applications fast and highly secure Book Description Ethereum is a blockchain-based, decentralized computing platform that allows running smart contracts. This book provides a basic overview of how Ethereum works, its ecosystem, mining process, and the consensus mechanism. It also demonstrates a step-by-step approach for building decentralized applications. This book begins with the very basics of Blockchain technology. Then it dives deep into the Ethereum architecture, framework and tools in its ecosystem. It also provides you an overview of ongoing research on Ethereum, for example, Layer 1 and 2 scaling solution, Stablecoin, ICO/STO/IEO, etc. Next, it explains Solidity language in detail, and provides step-by-step instructions for designing, developing, testing, deploying, and monitoring decentralized applications. In addition, you’ll learn how to use Truffle, Remix, Infura, Metamask, and many other Ethereum technologies. It’ll also help you develop your own cryptocurrency by creating ERC20, and ERC721 smart contracts from scratch. Finally, we explain private blockchains, and you learn how to interact with smart contracts through wallets. What you will learn * Understand the concepts of blockchain and cryptocurrency * Master Ethereum development tools such as Truffle, Remix IDE and Infura * Delve into smart contract development * Develop DApps frontend using Node.js, React.js, and Web3js API * Learn Etherscan and other tools to secure and monitor smart contracts * Develop and debug smart contracts by working with Remix * Apply Truffle suite to compile, migrate, and unit test smart contracts * Explore smart contracts such as ERC20 token and decentralized digital market Who this book is for This book is for all developers and architects who want to explore Ethereum blockchain fundamentals and get started with building real-world decentralized applications. Knowledge of an object-oriented programming language such as JavaScript will be useful but not mandatory.

An effective guide to designing, building, and deploying enterprise Java microservices with Eclipse MicroProfile Key Features * Create cloud-native microservices with ease using this detailed guide * Avoid vendor lock-in when implementing microservices using Eclipse MicroProfile * Discover why MicroProfile is a great specification for building microservices in multi-cloud environments Book Description Eclipse MicroProfile has gained momentum in the industry as a multi-vendor, interoperable, community-driven specification. It is a major disruptor that allows organizations with large investments in enterprise Java to move to microservices without spending a lot on retraining their workforce. This book is based on MicroProfile 2.2, however, it will guide you in running your applications in MicroProfile 3.0. You'll start by understanding why microservices are important in the digital economy and how MicroProfile addresses the need for enterprise Java microservices. You'll learn about the subprojects that make up a MicroProfile, its value proposition to organizations and developers, and its processes and governance. As you advance, the book takes you through the capabilities and code examples of MicroProfile’s subprojects - Config, Fault Tolerance, Health Check, JWT Propagation, Metrics, and OpenTracing. Finally, you’ll be guided in developing a conference application using Eclipse MicroProfile, and explore possible scenarios of what’s next in MicroProfile with Jakarta EE. By the end of this book, you'll have gained a clear understanding of Eclipse MicroProfile and its role in enterprise Java microservices. What you will learn * Understand why microservices are important in the digital economy * Analyze how MicroProfile addresses the need for enterprise Java microservices * Test and secure your applications with Eclipse MicroProfile * Get to grips with various MicroProfile capabilities such as OpenAPI and Typesafe REST Client * Explore reactive programming with MicroProfile Stream and Messaging candidate APIs * Discover and implement coding best practices using MicroProfile Who this book is for If you’re a Java developer who wants to create enterprise microservices, this book is for you. Familiarity with Java EE and the concept of microservices will help you get the most out of this book.

Integrate an end-to-end logistic chain using IBM Blockchain and IoT platforms Key Features *Explore practical implementation of ledger technology in the IoT architecture *Study security best practices for your smart devices *Understand Blockchain implementation for end-to-end IoT solutions Book Description Blockchain has been the hot topic of late thanks to cryptocurrencies. To make matters more interesting, the financial market is looking for ways to reduce operational costs and generate new business models, and this is where blockchain solutions come into the picture. In addition to this, with Internet of Things (IoT) trending and Arduino, Raspberry Pi, and other devices flooding the market, you can now create cheap devices even at home. Hands-On IoT Solutions with Blockchain starts with an overview of IoT concepts in the current business scenario. It then helps you develop your own device on the IBM Watson IoT platform and create your fi rst IoT solution using Watson and Intel Edison.Once you are familiar with IoT, you will learn about Blockchain technology and its use cases. You will also work with the Hyperledger framework and develop your own Blockchain network. As you progress through the chapters, you'll work with problem statements and learn how to design your solution architecture so that you can create your own integrated Blockchain and IoT solution. The next set of chapters will explain how to implement end-to-end Blockchain solutions with IoT using the IBM Cloud platform. By the end of this book, you will have mastered the convergence of IoT and Blockchain technology and exploited the best practices and drivers to develop a bulletproof integrated solution. What you will learn *Understand the key roles of IoT in the current market *Study the different aspects of IBM Watson IoT platform *Create devices, gateways, and applications connected to the platform *Explore the fundamentals of Blockchain *Define good use cases for Blockchain *Discover the Hyperledger Fabric and Composer frameworks *Develop an IBM Watson IoT application using a Intel Edison *Integrate IoT with the Blockchain platform Who this book is for Hands-On IoT Solutions with Blockchain is for you if you are an Internet of Things (IoT) analyst, architect, engineer, or any stakeholder responsible for security mechanisms on an IoT infrastructure. This book is also for IT professionals who want to start developing solutions using Blockchain and IoT on the IBM Cloud platform. Basic understanding of IoT will assist you in understanding key concepts covered in the book.

With loads of screenshots and illustrations and easy step-by-step instructions, this book is ideal for beginners in the network monitoring business. This book is for anyone who wants to manage a network using Cacti. You don't have to be a Linux Guru to use this book.

This book is a practical, handson guide that takes you through the techniques of web scraping using Beautiful Soup. Getting Started with Beautiful Soup is great for anybody who is interested in website scraping and extracting information. However, a basic knowledge of Python, HTML tags, and CSS is required for better understanding.

Build, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of real-world applications with complete Scala code. A concise guide to processing large-scale networks with Apache Spark. Who This Book Is For This book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. Basic programming experience with Scala is assumed. Basic knowledge of Spark is assumed. What You Will Learn Write, build and deploy Spark applications with the Scala Build Tool. Build and analyze large-scale network datasets Analyze and transform graphs using RDD and graph-specific operations Implement new custom graph operations tailored to specific needs. Develop iterative and efficient graph algorithms using message aggregation and Pregel abstraction Extract subgraphs and use it to discover common clusters Analyze graph data and solve various data science problems using real-world datasets. In Detail Apache Spark is the next standard of open-source cluster-computing engine for processing big data. Many practical computing problems concern large graphs, like the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. Apache Spark GraphX API combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. This book will teach the user to do graphical programming in Apache Spark, apart from an explanation of the entire process of graphical data analysis. You will journey through the creation of graphs, its uses, its exploration and analysis and finally will also cover the conversion of graph elements into graph structures. This book begins with an introduction of the Spark system, its libraries and the Scala Build Tool. Using a hands-on approach, this book will quickly teach you how to install and leverage Spark interactively on the command line and in a standalone Scala program. Then, it presents all the methods for building Spark graphs using illustrative network datasets. Next, it will walk you through the process of exploring, visualizing and analyzing different network characteristics. This book will also teach you how to transform raw datasets into a usable form. In addition, you will learn powerful operations that can be used to transform graph elements and graph structures. Furthermore, this book also teaches how to create custom graph operations that are tailored for specific needs with efficiency in mind. The later chapters of this book cover more advanced topics such as clustering graphs, implementing graph-parallel iterative algorithms and learning methods from graph data. Style and approach A step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical examples that will ensure an overall understanding of the concepts of Spark.

Extract valuable data from your social media sites and make better business decisions using R About This Book Explore the social media APIs in R to capture data and tame it Employ the machine learning capabilities of R to gain optimal business value A hands-on guide with real-world examples to help you take advantage of the vast opportunities that come with social media data Who This Book Is For If you have basic knowledge of R in terms of its libraries and are aware of different machine learning techniques, this book is for you. Those with experience in data analysis who are interested in mining social media data will find this book useful. What You Will Learn Access APIs of popular social media sites and extract data Perform sentiment analysis and identify trending topics Measure CTR performance for social media campaigns Implement exploratory data analysis and correlation analysis Build a logistic regression model to detect spam messages Construct clusters of pictures using the K-means algorithm and identify popular personalities and destinations Develop recommendation systems using Collaborative Filtering and the Apriori algorithm In Detail With an increase in the number of users on the web, the content generated has increased substantially, bringing in the need to gain insights into the untapped gold mine that is social media data. For computational statistics, R has an advantage over other languages in providing readily-available data extraction and transformation packages, making it easier to carry out your ETL tasks. Along with this, its data visualization packages help users get a better understanding of the underlying data distributions while its range of "standard" statistical packages simplify analysis of the data. This book will teach you how powerful business cases are solved by applying machine learning techniques on social media data. You will learn about important and recent developments in the field of social media, along with a few advanced topics such as Open Authorization (OAuth). Through practical examples, you will access data from R using APIs of various social media sites such as Twitter, Facebook, Instagram, GitHub, Foursquare, LinkedIn, Blogger, and other networks. We will provide you with detailed explanations on the implementation of various use cases using R programming. With this handy guide, you will be ready to embark on your journey as an independent social media analyst. Style and approach This easy-to-follow guide is packed with hands-on, step-by-step examples that will enable you to convert your real-world social media data into useful, practical information.

Over 90 hands-on recipes to design Internet scalable web and mobile applications with Amazon DynamoDB About This Book Construct top-notch mobile and web applications with the Internet scalable NoSQL database and host it on cloud Integrate your applications with other AWS services like AWS EMR, AWS S3, AWS Redshift, and AWS CloudSearch etc. in order to achieve a one-stop application stack Step-by-step implementation guide that provides real-world use with hands-on recipes Who This Book Is For This book is intended for those who have a basic understanding of AWS services and want to take their knowledge to the next level by getting their hands dirty with coding recipes in DynamoDB. What You Will Learn Design DynamoDB tables to achieve high read and write throughput Discover best practices like caching, exponential back-offs and auto-retries, storing large items in AWS S3, storing compressed data etc. Effectively use DynamoDB Local in order to make your development smooth and cost effective Implement cost effective best practices to reduce the burden of DynamoDB charges Create and maintain secondary indexes to support improved data access Integrate various other AWS services like AWS EMR, AWS CloudSearch, AWS Pipeline etc. with DynamoDB In Detail AWS DynamoDB is an excellent example of a production-ready NoSQL database. In recent years, DynamoDB has been able to attract many customers because of its features like high-availability, reliability and infinite scalability. DynamoDB can be easily integrated with massive data crunching tools like Hadoop /EMR, which is an essential part of this data-driven world and hence it is widely accepted. The cost and time-efficient design makes DynamoDB stand out amongst its peers. The design of DynamoDB is so neat and clean that it has inspired many NoSQL databases to simply follow it. This book will get your hands on some engineering best practices DynamoDB engineers use, which can be used in your day-to-day life to build robust and scalable applications. You will start by operating with DynamoDB tables and learn to manipulate items and manage indexes. You will also discover how to easily integrate applications with other AWS services like EMR, S3, CloudSearch, RedShift etc. A couple of chapters talk in detail about how to use DynamoDB as a backend database and hosting it on AWS ElasticBean. This book will also focus on security measures of DynamoDB as well by providing techniques on data encryption, masking etc. By the end of the book you’ll be adroit in designing web and mobile applications using DynamoDB and host it on cloud. Style and approach An easy-to-follow guide, full of real-world examples, which takes you through the world of DynamoDB following a step-by-step, problem-solution based approach.

Create exciting projects by connecting the Raspberry Pi to your Android phone About This Book Manage most of the fundamental functions of Raspberry Pi from your Android phone Use the projects created in this book to develop even more exciting projects in the future A project-based learning experience to help you discover amazing ways to combine the power of Android and Raspberry Pi Who This Book Is For The target audience for this book includes Raspberry Pi enthusiasts, hobbyists, and anyone who wants to create engaging projects with Android OS. Some knowledge of Android programming would be helpful. What You Will Learn Install the tools required on your Pi and Android to manage and administer the Pi from Android Share your files between different Android devices using the Pi as a server Set up the Pi to live-stream the camera in surveillance mode and customize Android to receive this content Turn your Pi into a media center and control it from your Android See your Android display on a large screen using Raspberry Pi Connect your car's dashboard to your Android device using Raspberry Pi In Detail Raspberry Pi is the credit card-sized, general purpose computer which has revolutionized portable technology. Android is an operating system that widely used in mobile phones today both on the high and low ends of the mobile phone market. However, there is little information about how to connect the two in spite of how popular both of them are. Raspberry Pi Android Projects starts with simple projects that help you access the command prompt and the desktop environment of Raspberry Pi from the comfort of your Android phone or tablet. Then, you will be introduced to more complex projects that combine the strengths of the Pi and Android in amazing ways. These projects will teach you how to manage services on the Pi from Android, share files between Android devices using the Pi as a server, administer and view the Pi’s camera from Android in surveillance mode, and connect your car to the Pi and make data more accessible using Android. The introductory projects covered will be useful each time you need to access or administer your Pi for other purposes, and the more advanced projects will continue to be valuable even after you become an expert on Pi. By the end of this book, you will be able to create engaging and useful projects that will help you combine the powers of both Android and Raspberry Pi. Style and approach A quick and easy-to-follow guide that will show how you can add up the power of Pi and Android by combining them.

Identify and resolve key Citrix XenAppissues using trusted troubleshooting and monitoring techniques About This BookUnderstand the key troubleshooting methodologies when working with XenApp 7.5 version and aboveUncover effective tips and techniques to solve real-world XenAppinfrastructure problemsThis is a fast-paced guide to developing key troubleshooting and problem resolution skills you can put to use in a Citrix environmentWho This Book Is ForThis book is for Citrix Administrators or Citrix Engineers who are currently managing Citrix XenAppin a production environment and want to learn how to troubleshoot XenAppissues in the shortest possible time. It is assumed that you have a basic understanding of XenApp’s components and how to implement and manage a XenAppinfrastructure.What You Will LearnGet to know about troubleshooting methodologies and perform a root cause analysis of the problemUnderstand the individual components and interactions required for a successful XenApp environmentsIdentify and troubleshoot issues around the core Citrix componentsIdentify XenAppcomponents and their roles and learn how they interact with the communication channelsGain tips and tricks to optimize Citrix deploymentsMonitor and optimize the XenAppenvironmentIn DetailCitrix XenAppis an application virtualization product from Citrix. It allows users to connect to their corporate applications from various computer systems and even mobile devices. XenApphas grown into a complex software with ever-expanding infrastructures in place. Together with tight integrations with other systems such as Terminal Services, Active Directory, and other third-party authentication services, troubleshooting XenApphas become more complicated.This book teaches you how to approach troubleshooting complex issues with XenAppdeployments and understand the problem, find a fix or workaround, determine the root cause, and apply corrective steps wherever applicable. The book progresses to give you an idea about the many supportive components that play an important role in XenApp’s application delivery model and should be considered while troubleshooting XenAppissues. It also shows you standard troubleshooting processes so that you can resolve complex XenAppissues in a mission critical environment.By the end of this book, you will see how and where to use supportive components that help minimize XenAppissues. Also, we’ll explain various tools that can be useful when monitoring and optimizing entire application and desktop delivery model.Style and approachThis is an easy-to-follow, fast-paced, example-oriented guide with a brief explanation on various troubleshooting methodologies to walk you through a host of real-life problems.

This book is intended for developers and Big Data engineers who want to know all about HBase at a hands-on level. For in-depth understanding, it would be helpful to have a bit of familiarity with HDFS and MapReduce programming concepts with no prior experience with HBase or similar technologies. This book is also for Big Data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic, scalable database solution in the Big Data space.

The book is intended for those who want to know more about network penetration tests and have no prior experience, as well as for those who are experienced in network systems and are interested in discovering more about this topic.

This book is an easytofollow guide, full of handson, realworld examples. Each topic is explained and demonstrated in a specific and userfriendly flow, from search optimization using Solr to Deployment of Zookeeper applications. This book is ideal for Apache Solr developers and want to learn different techniques to optimize Solr performance with utmost efficiency, along with effectively troubleshooting the problems that usually occur while trying to boost performance. Familiarity with search servers and database querying is expected.

This is a tutorial guide to gain in-depth knowledge such as realizing projects to migrate traditional telephony to Unified Communications inside an organization. This book is targeted at three audiences: business decision makers, technical advocates, and IT decision makers. As this is also a fundamental book on real time collaboration technology, it is also suitable for anyone who is interested in the future of communications.

An easytofollow, stepbystep tutorial focusing on practical situations and manipulations, guiding you to create a concrete Graphical User Interface and a simple 2D game. If you are a Unity 3D developer looking forward to learn NGUI for Unity, then this book is for you. Prior knowlege of C# *ing is expected. Additional knowledge of Unity 3D Editor, GameObject and creating/adding *s to GameObject would be beneficial; however, no prior knowledge of NGUI is required.