Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features * Get to grips with the fundamentals of deep learning and neural networks * Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processing * Implement effective deep learning systems in R with the help of end-to-end projects Book Description Deep learning finds practical applications in several domains, while R is the preferred language for designing and deploying deep learning models. This Learning Path introduces you to the basics of deep learning and even teaches you to build a neural network model from scratch. As you make your way through the chapters, you’ll explore deep learning libraries and understand how to create deep learning models for a variety of challenges, right from anomaly detection to recommendation systems. The book will then help you cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud, in addition to model optimization, overfitting, and data augmentation. Through real-world projects, you’ll also get up to speed with training convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs) in R. By the end of this Learning Path, you’ll be well versed with deep learning and have the skills you need to implement a number of deep learning concepts in your research work or projects. This Learning Path includes content from the following Packt products: * R Deep Learning Essentials - Second Edition by F. Wiley and Mark Hodnett * R Deep Learning Projects by Yuxi (Hayden) Liu and Pablo Maldonado What you will learn * Implement credit card fraud detection with autoencoders * Train neural networks to perform handwritten digit recognition using MXNet * Reconstruct images using variational autoencoders * Explore the applications of autoencoder neural networks in clustering and dimensionality reduction * Create natural language processing (NLP) models using Keras and TensorFlow in R * Prevent models from overfitting the data to improve generalizability * Build shallow neural network prediction models Who this book is for This Learning Path is for aspiring data scientists, data analysts, machine learning developers, and deep learning enthusiasts who are well versed in machine learning concepts and are looking to explore the deep learning paradigm using R. A fundamental understanding of R programming and familiarity with the basic concepts of deep learning are necessary to get the most out of this Learning Path.

Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages Key Features * Gain expertise in machine learning, deep learning and other techniques * Build intelligent end-to-end projects for finance, social media, and a variety of domains * Implement multi-class classification, regression, and clustering Book Description R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You'll tackle realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. You'll explore different clustering techniques to segment customers using wholesale data and use TensorFlow and Keras-R for performing advanced computations. You’ll also be introduced to reinforcement learning along with its various use cases and models. Additionally, it shows you how some of these black-box models can be diagnosed and understood. By the end of this Learning Path, you’ll be equipped with the skills you need to deploy machine learning techniques in your own projects. This Learning Path includes content from the following Packt products: * R Machine Learning Projects by Dr. Sunil Kumar Chinnamgari * Mastering Machine Learning with R - Third Edition by Cory Lesmeister What you will learn * Develop a joke recommendation engine to recommend jokes that match users’ tastes * Build autoencoders for credit card fraud detection * Work with image recognition and convolutional neural networks * Make predictions for casino slot machine using reinforcement learning * Implement NLP techniques for sentiment analysis and customer segmentation * Produce simple and effective data visualizations for improved insights * Use NLP to extract insights for text * Implement tree-based classifiers including random forest and boosted tree Who this book is for If you are a data analyst, data scientist, or machine learning developer this is an ideal Learning Path for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this Learning Path.

Design, deploy, and manage large-scale containers using Kubernetes Key Features * Gain insight into the latest features of Kubernetes, including Prometheus and API aggregation * Discover ways to keep your clusters always available, scalable, and up-to-date * Master the skills of designing and deploying large clusters on various cloud platforms Book Description If you are running a number of containers and want to be able to automate the way they’re managed, it can be helpful to have Kubernetes at your disposal. This Learning Path guides you through core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You'll get started by learning how to integrate your build pipeline and deployments in a Kubernetes cluster. As you cover more chapters in the Learning Path, you'll get up to speed with orchestrating updates behind the scenes, avoiding downtime on your cluster, and dealing with underlying cloud provider instability in your cluster. With the help of real-world use cases, you'll also explore options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you'll gain insights into custom resource development and utilization in automation and maintenance workflows. By the end of this Learning Path, you'll have the expertise you need to progress from an intermediate to an advanced level of understanding Kubernetes. This Learning Path includes content from the following Packt products: * Getting Started with Kubernetes - Third Edition by Jonathan Baier and Jesse White * Mastering Kubernetes - Second Edition by Gigi Sayfan What you will learn * Download, install, and configure the Kubernetes code base * Create and configure custom Kubernetes resources * Use third-party resources in your automation workflows * Deliver applications as standard packages * Set up and access monitoring and logging for Kubernetes clusters * Set up external access to applications running in the cluster * Manage and scale Kubernetes with hosted platforms on Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) * Run multiple clusters and manage them from a single control plane Who this book is for If you are a developer or a system administrator with an intermediate understanding of Kubernetes and want to master its advanced features, then this book is for you. Basic knowledge of networking is required to easily understand the concepts explained.

Apply cloud native patterns and practices to deliver responsive, resilient, elastic, and message-driven systems with confidence Key Features * Discover best practices for applying cloud native patterns to your cloud applications * Explore ways to effectively plan resources and technology stacks for high security and fault tolerance * Gain insight into core architectural principles using real-world examples Book Description Cloud computing has proven to be the most revolutionary IT development since virtualization. Cloud native architectures give you the benefit of more flexibility over legacy systems. This Learning Path teaches you everything you need to know for designing industry-grade cloud applications and efficiently migrating your business to the cloud. It begins by exploring the basic patterns that turn your database inside out to achieve massive scalability. You’ll learn how to develop cloud native architectures using microservices and serverless computing as your design principles. Then, you’ll explore ways to continuously deliver production code by implementing continuous observability in production. In the concluding chapters, you’ll learn about various public cloud architectures ranging from AWS and Azure to the Google Cloud Platform, and understand the future trends and expectations of cloud providers. By the end of this Learning Path, you’ll have learned the techniques to adopt cloud native architectures that meet your business requirements. This Learning Path includes content from the following Packt products: * Cloud Native Development Patterns and Best Practices by John Gilbert * Cloud Native Architectures by Erik Farr et al. What you will learn * Understand the difference between cloud native and traditional architecture * Automate security controls and configuration management * Minimize risk by evolving your monolithic systems into cloud native applications * Explore the aspects of migration, when and why to use it * Apply modern delivery and testing methods to continuously deliver production code * Enable massive scaling by turning your database inside out Who this book is for This Learning Path is designed for developers who want to progress into building cloud native systems and are keen to learn the patterns involved. Software architects, who are keen on designing scalable and highly available cloud native applications, will also find this Learning Path very useful. To easily grasp these concepts, you will need basic knowledge of programming and cloud computing.

If your application source code is overly verbose, it can be a nightmare to maintain. Write concise and expressive, type-safe code in an environment that lets you build for the JVM, browser, and more. Key Features *Expert guidance that shows you to efficiently use both object-oriented and functional programming techniques *Understand functional programming libraries, such as Cats and Scalaz, and use them to augment your Scala development *Perfectly balances theory and hands-on exercises, assessments, and activities Book Description This book teaches you how to build and contribute to Scala programs, recognizing common patterns and techniques used with the language. You’ll learn how to write concise, functional code with Scala. After an introduction to core concepts, syntax, and writing example applications with scalac, you’ll learn about the Scala Collections API and how the language handles type safety via static types out-of-the-box. You’ll then learn about advanced functional programming patterns, and how you can write your own Domain Specific Languages (DSLs). By the end of the book, you’ll be equipped with the skills you need to successfully build smart, efficient applications in Scala that can be compiled to the JVM. What you will learn *Understand the key language syntax and core concepts for application development *Master the type system to create scalable type-safe applications while cutting down your time spent debugging *Understand how you can work with advanced data structures via built-in features such as the Collections library *Use classes, objects, and traits to transform a trivial chatbot program into a useful assistant *Understand what are pure functions, immutability, and higher-order functions *Recognize and implement popular functional programming design patterns Who this book is for This is an ideal book for developers who are looking to learn Scala, and is particularly well suited for Java developers looking to migrate across to Scala for application development on the JVM.

Use an open source firewall and features such as failover, load balancer, OpenVPN, IPSec, and Squid to protect your network Key Features *Explore pfSense, a trusted open source network security solution *Configure pfSense as a firewall and create and manage firewall rules *Test pfSense for failover and load balancing across multiple WAN connections Book Description While connected to the internet, you’re a potential target for an array of cyber threats, such as hackers, keyloggers, and Trojans that attack through unpatched security holes. A firewall works as a barrier (or ‘shield’) between your computer and cyberspace. pfSense is highly versatile firewall software. With thousands of enterprises using pfSense, it is fast becoming the world's most trusted open source network security solution. Network Security with pfSense begins with an introduction to pfSense, where you will gain an understanding of what pfSense is, its key features, and advantages. Next, you will learn how to configure pfSense as a firewall and create and manage firewall rules. As you make your way through the chapters, you will test pfSense for failover and load balancing across multiple wide area network (WAN) connections. You will then configure pfSense with OpenVPN for secure remote connectivity and implement IPsec VPN tunnels with pfSense. In the concluding chapters, you’ll understand how to configure and integrate pfSense as a Squid proxy server. By the end of this book, you will be able to leverage the power of pfSense to build a secure network. What you will learn *Understand what pfSense is, its key features, and advantages *Configure pfSense as a firewall *Set up pfSense for failover and load balancing *Connect clients through an OpenVPN client *Configure an IPsec VPN tunnel with pfSense *Integrate the Squid proxy into pfSense Who this book is for Network Security with pfSense is for IT administrators, security administrators, technical architects, chief experience officers, and individuals who own a home or small office network and want to secure it.

A fast-paced guide to putting your GeoServer-based application into fast, user-friendly, and secure production Key Features * Resolve bottlenecks, optimize data stores, and cluster server resources * Use identity management and authentication for a user-specific, secure web application * Go beyond traditional web hosting to explore the full range of hosting options in the cloud Book Description GeoServer is open source, server-side software written in Java that allows users to share and edit geospatial data. In this book, you'll start by learning how to develop a spatial analysis platform with web processing services. Then you'll see how to develop an algorithm by chaining together geospatial analysis processes, which you can share with anyone in the world. Next you'll delve into a very important technique to improve the speed of your map application—tile caching. Here, you'll understand how tile caching works, how to develop an effective tile cache-supported web service, and how to leverage tile caching in your OpenLayers web application. Further on, you'll explore important tweaks to produce a performant GeoServer-backed web mapping application. Moving on, you'll enable authentication on the frontend and backend to protect sensitive map data, and deliver sensitive data to your end user. Finally, you'll see how to put your web application into production in a secure and user-friendly way. You'll go beyond traditional web hosting to explore the full range of hosting options in the cloud, and maintain a reliable server instance. What you will learn * Develop a WPS-processing service to allow web-based geospatial data processing * Get to know important techniques to improve the speed of your web map application—tile caching, raster data optimization, and server clustering * Find out which GeoServer settings resolve bottlenecks * Develop an algorithm by chaining geospatial analysis processes together * Put your application into production with hosting, monitoring, and automated backup and recovery * Understand how to develop an effective tile cache-supported web service * Master techniques that ensure resilient server deployment Who this book is for This book is for anyone who wants to learn about advanced interfaces, security, and troubleshooting techniques in GeoServer. A basic understanding of GeoServer is required

If you are a web developer with some experience in JavaScript and want to enter the world of modern web applications, then this book is ideal for you. Learning how to leverage the three tools (Yo, Bower, and Grunt) in the Yeoman workflow will be perfect as your next step towards building scalable, dynamic, and modern web applications for just about any platform.

VMware vSphere 6.5: Deployment, Migration, Patch-Management

A solution-based guide to put your deep learning models into production with the power of Apache Spark Key Features * Discover practical recipes for distributed deep learning with Apache Spark * Learn to use libraries such as Keras and TensorFlow * Solve problems in order to train your deep learning models on Apache Spark Book Description With deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries. As a result, this will help deep learning models train with higher efficiency and speed. With the help of the Apache Spark Deep Learning Cookbook, you’ll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you’ll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you’ll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras. By the end of the book, you'll have the expertise to train and deploy efficient deep learning models on Apache Spark. What you will learn * Set up a fully functional Spark environment * Understand practical machine learning and deep learning concepts * Apply built-in machine learning libraries within Spark * Explore libraries that are compatible with TensorFlow and Keras * Explore NLP models such as Word2vec and TF-IDF on Spark * Organize dataframes for deep learning evaluation * Apply testing and training modeling to ensure accuracy * Access readily available code that may be reusable Who this book is for If you’re looking for a practical and highly useful resource for implementing efficiently distributed deep learning models with Apache Spark, then the Apache Spark Deep Learning Cookbook is for you. Knowledge of the core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the best out of this book. Additionally, some programming knowledge in Python is a plus.

Leverage the power of Hyperledger Fabric to develop Blockchain-based distributed ledgers with ease About This Book ? Write your own chaincode/smart contracts using Golang on hyperledger network ? Build and deploy decentralized applications (DApps) ? Dive into real world blockchain challenges such as integration and scalability Who This Book Is For The book benefits business leaders as it provides a comprehensive view on blockchain business models, governance structure, and business design considerations of blockchain solutions. Technology leaders stand to gain a lot from the detailed discussion around the technology landscape, technology design, and architecture considerations in the book. With model-driven application development, this guide will speed up understanding and concept development for blockchain application developers. The simple and well organized content will put novices at ease with blockchain concepts and constructs. What You Will Learn ? Discover why blockchain is a game changer in the technology landscape ? Set up blockchain networks using basic Hyperledger Fabric deployment ? Understand the considerations for creating decentralized applications ? Learn the process of creating good business networks using Hyperledger ? Write Smart Contracts quickly with Hyperledger Composer ? Design transaction model and chaincode with Golang ? Deploy Composer REST Gateway to access the Composer transactions ? Discern how business network impacts your Hyperledger Fabric solutions In Detail Blockchain and Hyperledger technologies are hot topics. Hyperledger Fabric and Hyperledger Composer are open source projects that help organizations create private, permissioned blockchain networks. Applications that exploit them include finance, banking, supply chains, IoT, and much more. This book will be an easy reference to explore and build blockchain networks using Hyperledger technologies. This book will start by explaining the blockchain evolution, including an overview of relevant blockchain technologies. You will learn how to configure Hyperledger Fabric on a cloud platform. Understand the architectural components of Hyperledger Fabric, and how they are configured to build private blockchain networks, and applications that connect to them. You'll build up a network and application from scratch, starting with first principles. You'll learn how to implement smart contracts in chaincode and much more on the Hyperledger network. By the end of this book, you will be able to build and deploy your own decentralized applications using Hyperledger, addressing the key pain points encountered in the blockchain life cycle. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Hyperledger

Improve the speed of your code and optimize the performance of your apps About This Book ? Understand the common performance pitfalls and improve your application’s performance ? Get to grips with multi-threaded and asynchronous programming in C# ? Develop highly performant applications on .NET Core using microservice architecture Who This Book Is For This book is for .NET developers looking at improving the speed of their code or simply wanting to take their skills to the next level. Basic C# knowledge is assumed. What You Will Learn ? Measure application performance using BenchmarkDotNet ? Explore the techniques to write multithreaded applications ? Leverage TPL and PLinq libraries to perform asynchronous operations ? Get familiar with data structures to write optimized code ? Understand design techniques to increase your application’s performance ? Learn about memory management techniques in .NET Core ? Develop a containerized application based on microservices architecture ? Learn tools and techniques to monitor application performance In Detail While writing an application, performance is paramount. Performance tuning for realworld applications often involves activities geared toward fnding bottlenecks; however, this cannot solve the dreaded problem of slower code. If you want to improve the speed of your code and optimize an application's performance, then this book is for you. C# 7 and .NET Core 2.0 High Performance begins with an introduction to the new features of what?explaining how they help in improving an application's performance. Learn to identify the bottlenecks in writing programs and highlight common performance pitfalls, and learn strategies to detect and resolve these issues early. You will explore multithreading and asynchronous programming with .NET Core and learn the importance and effcient use of data structures. This is followed with memory management techniques and design guidelines to increase an application’s performance. Gradually, the book will show you the importance of microservices architecture for building highly performant applications and implementing resiliency and security in .NET Core. After reading this book, you will learn how to structure and build scalable, optimized, and robust applications in C#7 and .NET. Style and approach This book will be a step by step easy to follow guide with focused examples to increase performance of applications and provide optimization techniques.

A definitive guide to creating an intelligent web application with the best of machine learning and JavaScript About This Book ? Solve complex computational problems in browser with JavaScript ? Teach your browser how to learn from rules using the power of machine learning ? Understand discoveries on web interface and API in machine learning Who This Book Is For This book is for you if you are a JavaScript developer who wants to implement machine learning to make applications smarter, gain insightful information from the data, and enter the field of machine learning without switching to another language. Working knowledge of JavaScript language is expected to get the most out of the book. What You Will Learn ? Get an overview of state-of-the-art machine learning ? Understand the pre-processing of data handling, cleaning, and preparation ? Learn Mining and Pattern Extraction with JavaScript ? Build your own model for classification, clustering, and prediction ? Identify the most appropriate model for each type of problem ? Apply machine learning techniques to real-world applications ? Learn how JavaScript can be a powerful language for machine learning In Detail In over 20 years of existence, JavaScript has been pushing beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars, and more. Today, with the added advantage of machine learning research and support for JS libraries, JavaScript makes your browsers smarter than ever with the ability to learn patterns and reproduce them to become a part of innovative products and applications. Hands-on Machine Learning with JavaScript presents various avenues of machine learning in a practical and objective way, and helps implement them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, and building neural models are some of the skills you will build from this book. You will learn how to train your machine learning models and work with different kinds of data. During this journey, you will come across use cases such as face detection, spam filtering, recommendation systems, character recognition, and more. Moreover, you will learn how to work with deep neural networks and guide your applications to gain insights from data. By the end of this book, you'll have gained hands-on knowledge on evaluating and implementing the right model, along with choosing from different JS libraries, such as NaturalNode, brain, harthur, classifier, and many more to design smarter applications. Style and approach This is a practical tutorial that uses hands-on examples to step through some real-world applications of machine learning. Without shying away from the technical details, you will explore machine learning with JavaScript using clear and practical examples.

Leverage the power of Python to build DIY robotic projects About This Book ? Design, build, and stimulate collaborative robots ? Build high-end robotics projects such as a customized personal Jarvis ? Leverage the power of Python and ROS for DIY robotic projects Who This Book Is For If building robots is your dream, then this book is made for you. Prior knowledge of Python would be an added advantage. What You Will Learn ? Get to know the basics of robotics and its functions ? Walk through interface components with microcontrollers ? Integrate robotics with the IoT environment ? Build projects using machine learning ? Implement path planning and vision processing ? Interface your robots with Bluetooth In Detail Robotics is a fast-growing industry. Multiple surveys state that investment in the field has increased tenfold in the last 6 years, and is set to become a $100-billion sector by 2020. Robots are prevalent throughout all industries, and they are all set to be a part of our domestic lives. This book starts with the installation and basic steps in configuring a robotic controller. You'll then move on to setting up your environment to use Python with the robotic controller. You'll dive deep into building simple robotic projects, such as a pet-feeding robot, and more complicated projects, such as machine learning enabled home automation system (Jarvis), vision processing based robots and a self-driven robotic vehicle using Python. By the end of this book, you'll know how to build smart robots using Python. Style and approach A simple step-by-step guide to help you learn the concepts of robotics using simple to advanced steps. You’ll not only learn the concepts of AI, machine learning, and Vision Processing, but also how to practically implement them in your projects.

Get started with designing your serverless application using optimum design patterns and industry standard practices About This Book ? Learn the details of popular software patterns and how they are applied to serverless applications ? Understand key concepts and components in serverless designs ? Walk away with a thorough understanding of architecting serverless applications Who This Book Is For If you're a software architect, engineer, or someone who wants to build serverless applications, which are non-trivial in complexity and scope, then this book is for you. Basic knowledge of programming and serverless computing concepts are assumed. What You Will Learn ? Comprehend the popular design patterns currently being used with serverless architectures ? Understand the various design options and corresponding implementations for serverless web application APIs ? Learn multiple patterns for data-intensive serverless systems and pipelines, including MapReduce and Lambda Architecture ? Learn how to leverage hosted databases, queues, streams, storage services, and notification services ? Understand error handling and system monitoring in a serverless architecture a serverless architecture ? Learn how to set up a serverless application for continuous integration, continuous delivery, and continuous deployment In Detail Serverless applications handle many problems that developers face when running systems and servers. The serverless pay-per-invocation model can also result in drastic cost savings, contributing to its popularity. While it's simple to create a basic serverless application, it's critical to structure your software correctly to ensure it continues to succeed as it grows. Serverless Design Patterns and Best Practices presents patterns that can be adapted to run in a serverless environment. You will learn how to develop applications that are scalable, fault tolerant, and well-tested. The book begins with an introduction to the different design pattern categories available for serverless applications. You will learn the trade-offs between GraphQL and REST and how they fare regarding overall application design in a serverless ecosystem. The book will also show you how to migrate an existing API to a serverless backend using AWS API Gateway. You will learn how to build event-driven applications using queuing and streaming systems, such as AWS Simple Queuing Service (SQS) and AWS Kinesis. Patterns for data-intensive serverless application are also explained, including the lambda architecture and MapReduce. This book will equip you with the knowledge and skills you need to develop scalable and resilient serverless applications confidently. Style and approach Readers will be taken through a set of specific software patterns and learn, in detail, how to apply these patterns and build working software on top of a serverless system. At each step along the way, the reader will learn about the subcomponents and subsystems which comprise the larger system and which may be used in the future to solve different types of challenges.

Learn how to implement the reactive programming paradigm with C++ and build asynchronous and concurrent applications About This Book ? Efficiently exploit concurrency and parallelism in your programs ? Use the Functional Reactive programming model to structure programs ? Understand reactive GUI programming to make your own applications using Qt Who This Book Is For If you’re a C++ developer interested in using reactive programming to build asynchronous and concurrent applications, you’ll find this book extremely useful. This book doesn’t assume any previous knowledge of reactive programming. What You Will Learn ? Understand language-level concurrency in C++ ? Explore advanced C++ programming for the FRP ? Uncover the RxCpp library and its programming model ? Mix the FP and OOP constructs in C++ 17 to write well-structured programs ? Master reactive microservices in C++ ? Create custom operators for RxCpp ? Learn advanced stream processing and error handling In Detail Reactive programming is an effective way to build highly responsive applications with an easy-to-maintain code base. This book covers the essential functional reactive concepts that will help you build highly concurrent, event-driven, and asynchronous applications in a simpler and less error-prone way. C++ Reactive Programming begins with a discussion on how event processing was undertaken by different programming systems earlier. After a brisk introduction to modern C++ (C++17), you’ll be taken through language-level concurrency and the lock-free programming model to set the stage for our foray into the Functional Programming model. Following this, you’ll be introduced to RxCpp and its programming model. You’ll be able to gain deep insights into the RxCpp library, which facilitates reactive programming. You’ll learn how to deal with reactive programming using Qt/C++ (for the desktop) and C++ microservices for the Web. By the end of the book, you will be well versed with advanced reactive programming concepts in modern C++ (C++17). Style and approach The book includes real-world problems that you will solve with the reactive programming model. It highlights the way event processing has evolved in the programming world.

Build enterprise-grade microservice ecosystems with intensive case studies using C# About This Book ? Learn to build message-based microservices ? Packed with case studies to explain the intricacies of large-scale microservices ? Build scalable, modular, and robust architectures with C# Who This Book Is For C# developers, software architects, and professionals who want to master the art of designing the microservice architecture that is scalable based on environment. Developers should have a basic understanding of.NET application development using C# and Visual Studio What You Will Learn ? Explore different open source tools within the context of designing microservices ? Learn to provide insulation to exception-prone function calls ? Build common messages used between microservices for communication ? Learn to create a microservice using our base class and interface ? Design a quantitative financial machine microservice ? Learn to design a microservice that is capable of using Blockchain technology In Detail C# is a powerful language when it comes to building applications and software architecture using rich libraries and tools such as .NET. This book will harness the strength of C# in developing microservices architectures and applications. This book shows developers how to develop an enterprise-grade, event-driven, asynchronous, message-based microservice framework using C#, .NET, and various open source tools. We will discuss how to send and receive messages, how to design many types of microservice that are truly usable in a corporate environment. We will also dissect each case and explain the code, best practices, pros and cons, and more. Through our journey, we will use many open source tools, and create file monitors, a machine learning microservice, a quantitative financial microservice that can handle bonds and credit default swaps, a deployment microservice to show you how to better manage your deployments, and memory, health status, and other microservices. By the end of this book, you will have a complete microservice ecosystem you can place into production or customize in no time. Style and approach A step-by-step guide that enables readers to create a complete microservice ecosystem they can place into production or customize in no time.

Use Java features such as JAX-RS, EJBs, and JPAs to build powerful middleware for newer architectures such as the cloud About This Book ? Explore EJBs to build middleware solutions for enterprise and distributed applications ? Understand middleware designs such as event-based and message-driven web services ? Learn to design and maintain large-scale systems and vendor disputes Who This Book Is For Enterprise architects, designers, developers, and programmers who are interested in learning how to build robust middleware solutions for enterprise software will find this book useful. Prior knowledge of Java EE is essential What You Will Learn ? Implement the latest Java EE 8 APIs and manage dependencies with CDI 2.0 ? Perform CRUD operations and access databases with JPA 2.1 ? Use bean validation API 2.0 to validate data ? Develop business logic with EJB 3.2 ? Incorporate the REST architecture and RESTful API design patterns ? Perform serialization and deserialization on JSON documents using JSON-B ? Utilize JMS for messaging and queuing models and securing applications ? Test applications using JUnit and Mockito and deploy them using Docker In Detail Middleware is the infrastructure in software based applications that enables businesses to solve problems, operate more efficiently, and make money. As the use of middleware extends beyond a single application, the importance of having it written by experts increases substantially. This book will help you become an expert in developing middleware for a variety of applications. The book starts off by exploring the latest Java EE 8 APIs with newer features and managing dependencies with CDI 2.0. You will learn to implement object-to-relational mapping using JPA 2.1 and validate data using bean validation. You will also work with different types of EJB to develop business logic, and with design RESTful APIs by utilizing different HTTP methods and activating JAX-RS features in enterprise applications. You will learn to secure your middleware with Java Security 1.0 and implement various authentication techniques, such as OAuth authentication. In the concluding chapters, you will use various test technologies, such as JUnit and Mockito, to test applications, and Docker to deploy your enterprise applications. By the end of the book, you will be proficient in developing robust, effective, and distributed middleware for your business. Style and approach Learn how to design and implement professional enterprise middleware solutions using the latest techniques and features provided by the Java EE 8 platform.

Build next-generation Artificial Intelligence systems with Java About This Book ? Implement AI techniques to build smart applications using Deeplearning4j ? Perform big data analytics to derive quality insights using Spark MLlib ? Create self-learning systems using neural networks, NLP, and reinforcement learning Who This Book Is For This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus. What You Will Learn ? Manage Artificial Intelligence techniques for big data with Java ? Build smart systems to analyze data for enhanced customer experience ? Learn to use Artificial Intelligence frameworks for big data ? Understand complex problems with algorithms and Neuro-Fuzzy systems ? Design stratagems to leverage data using Machine Learning process ? Apply Deep Learning techniques to prepare data for modeling ? Construct models that learn from data using open source tools ? Analyze big data problems using scalable Machine Learning algorithms In Detail In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. Style and approach An easy-to-follow, step-by-step guide to help you get to grips with real-world applications of Artificial Intelligence for big data using Java

Learn about cryptography and cryptocurrencies, so you can build highly secure, decentralized applications and conduct trusted in-app transactions. About This Book ? Get to grips with the underlying technical principles and implementations of blockchain ? Build powerful applications using Ethereum to secure transactions and create smart contracts ? Explore cryptography, mine cryptocurrencies, and solve scalability issues with this comprehensive guide Who This Book Is For This book will appeal to those who wish to build fast, highly secure, transactional applications. It targets people who are familiar with the concept of blockchain and are comfortable with a programming language. What You Will Learn ? Master the theoretical and technical foundations of the blockchain technology ? Understand the concept of decentralization, its impact, and its relationship with blockchain technology ? Master how cryptography is used to secure data - with practical examples ? Grasp the inner workings of blockchain and the mechanisms behind bitcoin and alternative cryptocurrencies ? Understand the theoretical foundations of smart contracts ? Learn how Ethereum blockchain works and how to develop decentralized applications using Solidity and relevant development frameworks ? Identify and examine applications of the blockchain technology - beyond currencies ? Investigate alternative blockchain solutions including Hyperledger, Corda, and many more ? Explore research topics and the future scope of blockchain technology In Detail A blockchain is a distributed ledger that is replicated across multiple nodes and enables immutable, transparent and cryptographically secure record-keeping of transactions. The blockchain technology is the backbone of cryptocurrencies, and it has applications in finance, government, media and almost all other industries. Mastering Blockchain, Second Edition has been thoroughly updated and revised to provide a detailed description of this leading technology and its implementation in the real world. This book begins with the technical foundations of blockchain technology, teaching you the fundamentals of distributed systems, cryptography and how it keeps data secure. You will learn about the mechanisms behind cryptocurrencies and how to develop applications using Ethereum, a decentralized virtual machine. You will also explore different other blockchain solutions and get an introduction to business blockchain frameworks under Hyperledger, a collaborative effort for the advancement of blockchain technologies hosted by the Linux Foundation. You will also be shown how to implement blockchain solutions beyond currencies, Internet of Things with blockchain, blockchain scalability, and the future scope of this fascinating and powerful technology. Style and approach This comprehensive guide allows you to build smart blockchain applications and explore the power of this database. The book will let you quickly brush up on the basics of the blockchain database, followed by advanced implementations of blockchain in currency, smart contracts, decentralization, and so on.

Make the most of Kotlin by leveraging design patterns and best practices to build scalable and high performing apps About This Book ? Understand traditional GOF design patterns to apply generic solutions ? Shift from OOP to FP; covering reactive and concurrent patterns in a step-by-step manner ? Choose the best microservices architecture and MVC for your development environment Who This Book Is For This book is for developers who would like to master design patterns with Kotlin to build efficient and scalable applications. Basic Java or Kotlin programming knowledge is assumed What You Will Learn ? Get to grips with Kotlin principles, including its strengths and weaknesses ? Understand classical design patterns in Kotlin ? Explore functional programming using built-in features of Kotlin ? Solve real-world problems using reactive and concurrent design patterns ? Use threads and coroutines to simplify concurrent code flow ? Understand antipatterns to write clean Kotlin code, avoiding common pitfalls ? Learn about the design considerations necessary while choosing between architectures In Detail Design patterns enable you as a developer to speed up the development process by providing you with proven development paradigms. Reusing design patterns helps prevent complex issues that can cause major problems, improves your code base, promotes code reuse, and makes an architecture more robust. The mission of this book is to ease the adoption of design patterns in Kotlin and provide good practices for programmers. The book begins by showing you the practical aspects of smarter coding in Kotlin, explaining the basic Kotlin syntax and the impact of design patterns. From there, the book provides an in-depth explanation of the classical design patterns of creational, structural, and behavioral families, before heading into functional programming. It then takes you through reactive and concurrent patterns, teaching you about using streams, threads, and coroutines to write better code along the way By the end of the book, you will be able to efficiently address common problems faced while developing applications and be comfortable working on scalable and maintainable projects of any size. Style and approach This book explains design patterns in a step-by-step manner with clear and concise code examples