Discover Android programming and web development by understanding the concepts of Kotlin Programming About This Book ? Practical solutions to your common programming problems with Kotlin 1.1 ? Leverage the functional power of Kotlin to ease your Android application development ? Learn to use Java code in conjunction with Kotlin Who This Book Is For This book will appeal to Kotlin developers keen to find solutions for their common programming problems. Java programming knowledge would be an added advantage. What You Will Learn ? Understand the basics and object-oriented concepts of Kotlin Programming ? Explore the full potential of collection frameworks in Kotlin ? Work with SQLite databases in Android, make network calls, and fetch data over a network ? Use Kotlin's Anko library for efficient and quick Android development ? Uncover some of the best features of Kotlin: Lambdas and Delegates ? Set up web service development environments, write servlets, and build RESTful services with Kotlin ? Learn how to write unit tests, integration tests, and instrumentation/acceptance tests. In Detail The Android team has announced first-class support for Kotlin 1.1. This acts as an added boost to the language and more and more developers are now looking at Kotlin for their application development. This recipe-based book will be your guide to learning the Kotlin programming language. The recipes in this book build from simple language concepts to more complex applications of the language. After the fundamentals of the language, you will learn how to apply the object-oriented programming features of Kotlin 1.1. Programming with Lambdas will show you how to use the functional power of Kotlin. This book has recipes that will get you started with Android programming with Kotlin 1.1, providing quick solutions to common problems encountered during Android app development. You will also be taken through recipes that will teach you microservice and concurrent programming with Kotlin. Going forward, you will learn to test and secure your applications with Kotlin. Finally, this book supplies recipes that will help you migrate your Java code to Kotlin and will help ensure that it's interoperable with Java. Style and approach This book explains concepts related to Kotlin Programming using a practical approach and with the help of easy-to-follow recipes.

Get to grips with the essentials of deep learning by leveraging the power of Python About This Book ? Your one-stop solution to get started with the essentials of deep learning and neural network modeling ? Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more ? Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Who This Book Is For Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python. What You Will Learn ? Get to grips with the core concepts of deep learning and neural networks ? Set up deep learning library such as TensorFlow ? Fine-tune your deep learning models for NLP and Computer Vision applications ? Unify different information sources, such as images, text, and speech through deep learning ? Optimize and fine-tune your deep learning models for better performance ? Train a deep reinforcement learning model that plays a game better than humans ? Learn how to make your models get the best out of your GPU or CPU In Detail Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. Style and approach This step-by-step guide is filled with real-world practical examples and use cases to solve various deep learning problems.

Gain comprehensive insight into WPF mechanics and capabilities. About This Book ? Gain a strong foundation in WPF features and patterns ? Leverage the MVVM pattern to build decoupled, maintainable apps ? Increase efficiency through Performance tuning and UI automation Who This Book Is For The book is intended for developers who are relatively new to WPF (Windows Presentation Foundation), or those who have been working with WPF for some time, but want to get a deeper understanding of its foundation and concepts to gain practical knowledge. Basic knowledge of C# and Visual Studio is assumed. What You Will Learn ? Understand the fundamentals of WPF ? Explore the major controls and manage element layout ? Implement data binding ? Create custom elements that lead to a particular implementation path ? Customize controls, styles, and templates in XAML ? Leverage the MVVM pattern to maintain a clean and reusable structure in your code ? Master practical animations ? Integrate WCF services in a WPF application ? Implement WPFs support for debugging and asynchronous operations In Detail Windows Presentation Foundation (WPF) is Microsoft's development tool for building rich Windows client user experiences that incorporate UIs, media, and documents. With the updates in .NET 4.7, Visual Studio 2017, C# 7, and .NET Standard 2.0, WPF has taken giant strides and is now easier than ever for developers to use. If you want to get an in-depth view of WPF mechanics and capabilities, then this book is for you. The book begins by teaching you about the fundamentals of WPF and then quickly shows you the standard controls and the layout options. It teaches you about data bindings and how to utilize resources and the MVVM pattern to maintain a clean and reusable structure in your code. After this, you will explore the animation capabilities of WPF and see how they integrate with other mechanisms. Towards the end of the book, you will learn about WCF services and explore WPF's support for debugging and asynchronous operations. By the end of the book, you will have a deep understanding of WPF and will know how to build resilient applications. Style and approach This book takes a recipe-based approach to teaching you how to create fault-tolerant WPF applications.

A tutorial leading the aspiring Go developer to full mastery of Golang's distributed features. About This Book ? This book provides enough concurrency theory to give you a contextual understanding of Go concurrency ? It gives weight to synchronous and asynchronous data streams in Golang web applications ? It makes Goroutines and Channels completely familiar and natural to Go developers Who This Book Is For This book is for developers who are familiar with the Golang syntax and have a good idea of how basic Go development works. It would be advantageous if you have been through a web application product cycle, although it’s not necessary. What You Will Learn ? Gain proficiency with concurrency and parallelism in Go ? Learn how to test your application using Go's standard library ? Learn industry best practices with technologies such as REST, OpenAPI, Docker, and so on ? Design and build a distributed search engine ? Learn strategies on how to design a system for web scale In Detail Distributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you’ll learn the basic concepts and practices of Golang concurrent and parallel development. You’ll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you’ll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands. Another use case is the way in which a web application written in Go can be consciously redesigned to take distributed features into account. The chapter is rather interesting for Go developers who have to migrate existing Go applications to computationally and memory-intensive environments. The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula. Style and approach Distributed Computing with Go takes you through a series of carefully graded tutorials, building ever more sophisticated applications.

A practical guide designed to get you from basics to current state of art in computer vision systems. About This Book ? Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease ? Leverage the power of Python, Tensorflow, Keras, and OpenCV to perform image processing, object detection, feature detection and more ? With real-world datasets and fully functional code, this book is your one-stop guide to understanding Computer Vision Who This Book Is For This book is for machine learning practitioners and deep learning enthusiasts who want to understand and implement various tasks associated with Computer Vision and image processing in the most practical manner possible. Some programming experience would be beneficial while knowing Python would be an added bonus. What You Will Learn ? Learn the basics of image manipulation with OpenCV ? Implement and visualize image filters such as smoothing, dilation, histogram equalization, and more ? Set up various libraries and platforms, such as OpenCV, Keras, and Tensorflow, in order to start using computer vision, along with appropriate datasets for each chapter, such as MSCOCO, MOT, and Fashion-MNIST ? Understand image transformation and downsampling with practical implementations. ? Explore neural networks for computer vision and convolutional neural networks using Keras ? Understand working on deep-learning-based object detection such as Faster-R-CNN, SSD, and more ? Explore deep-learning-based object tracking in action ? Understand Visual SLAM techniques such as ORB-SLAM In Detail In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects. With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications. Style and approach Step-by-step guide filled with real-world, practical examples for understanding and applying various Computer Vision techniques

Get command of your organizational Big Data using the power of data science and analytics About This Book ? A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions ? Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses ? Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Who This Book Is For The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience. What You Will Learn ? Get a 360-degree view into the world of Big Data, data science and machine learning ? Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives ? Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R ? Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions ? Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications ? Understand corporate strategies for successful Big Data and data science projects ? Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies In Detail Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. Style and approach This book equips you with a knowledge of various NoSQL tools, R, Python programming, cloud platforms, and techniques so you can use them to store, analyze, and deliver meaningful insights from your data.

Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book ? Learn how to apply complex visual effects to images with OpenCV 3.x and Python ? Extract features from an image and use them to develop advanced applications ? Build algorithms to help you understand image content and perform visual searches ? Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn ? Detect shapes and edges from images and videos ? How to apply filters on images and videos ? Use different techniques to manipulate and improve images ? Extract and manipulate particular parts of images and videos ? Track objects or colors from videos ? Recognize specific object or faces from images and videos ? How to create Augmented Reality applications ? Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. Style and approach The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.

Transform yourself into a Kubernetes specialist in serverless applications. About This Book ? Get hands-on experience in installing, configuring, and using services such as Kubeless, Funktion, OpenWhisk, and Fission ? Learn how to launch Kubernetes both locally and in public clouds ? Explore the differences between using services such as AWS Lambda and Azure Functions and running your own Who This Book Is For If you are a DevOps engineer, cloud architect, or a stakeholder keen to learn about serverless functions in Kubernetes environments, then this book is for you. What You Will Learn ? Get a detailed analysis of serverless/Functions as a Service ? Get hands-on with installing and running tasks in Kubernetes using Minikube ? Install Kubeless locally and launch your first function. ? Launch Kubernetes in the cloud and move your applications between your local machine and your cloud cluster ? Deploy applications on Kubernetes using Apache OpenWhisk ? Explore topics such as Funktion and Fission installation on the cloud followed by launching applications ? Monitor a serverless function and master security best practices and Kubernetes use cases In Detail Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. It has been adopted by companies such as Google, its original developers, and Microsoft as an integral part of their public cloud platforms, so that you can develop for Kubernetes and not worry about being locked into a single vendor. This book will initially start by introducing serverless functions. Then you will configure tools such as Minikube to run Kubernetes. Once you are up-and-running, you will install and configure Kubeless, your first step towards running Function as a Service (FaaS) on Kubernetes. Then you will gradually move towards running Fission, a framework used for managing serverless functions on Kubernetes environments. Towards the end of the book, you will also work with Kubernetes functions on public and private clouds. By the end of this book, we will have mastered using Function as a Service on Kubernetes environments. Style and approach A clear, concise, and straightforward book that will empower you work with clusters and run serverless functions effectively.

Deploy and manage VMware vSphere 6.5 components with ease. About This Book ? Simplified and to-the-point theory and practical recipes to deploy and manage vSphere 6.5 ? Discover the best ways to deploy stateless and stateful ESXi hosts and upgrade them ? Storage and network resource management ? Certificate management using VMCA ? Monitor the performance of a vSphere environment. Who This Book Is For If you are a system administrator, support professional, or anyone interested in learning how to install, configure, and manage a vSphere environment, then this book is for you. This task-oriented reference guide will also benefit consultants or infrastructure architects who design and deploy vSphere 6.5 environments. What You Will Learn ? Upgrade your existing vSphere environment or perform a fresh deployment. ? Automate the deployment and management of large sets of ESXi hosts in your vSphere Environment ? Configure and manage FC, iSCSI, and NAS storage, and get more control over how storage resources are allocated and managed ? Configure vSphere networking by deploying host-wide and data center-wide switches in your vSphere environment ? Configure high availability on a host cluster and learn how to enable the fair distribution and utilization of compute resources ? Patch and upgrade the vSphere environment ? Handle certificate request generation and renew component certificates ? Monitor performance of a vSphere environment In Detail VMware vSphere is a complete and robust virtualization product suite that helps transform data centers into simplified on-premises cloud infrastructures, providing for the automation and orchestration of workload deployment and life cycle management of the infrastructure. This book focuses on the latest release of VMware vSphere and follows a recipe-based approach, giving you hands-on instructions required to deploy and manage a vSphere environment. The book starts with the procedures involved in upgrading your existing vSphere infrastructure to vSphere 6.5, followed by deploying a new vSphere 6.5 environment. Then the book delves further into the procedures involved in managing storage and network access to the ESXi hosts and the virtual machines running on them. Moving on, the book covers high availability and fair distribution/utilization of clustered compute and storage resources. Finally, the book covers patching and upgrading the vSphere infrastructure using VUM, certificate management using VMCA, and finishes with a chapter covering the tools that can be used to monitor the performance of a vSphere infrastructure. Style and approach This book will quickly get you started with managing VMware components.

This book gets you started and gives you knowledge about AWS Fargate in order to successfully incorporate it in your ECS container application. Key Features *Gives you a quick walk-through over the Amazon Elastic Container Services (ECS) *Provides an in depth knowledge of the components that Amazon Fargate has to offer. *Learn the practical aspects of Docker application development with a managed service Book Description Amazon Fargate is new launch type for the Amazon Elastic Container Service (ECS). ECS is an AWS service for Docker container orchestration. Docker is the de facto containerization framework and has revolutionized packaging and deployment of software. The introduction of Fargate has made the ECS platform serverless. The book takes you through how Amazon Fargate runs ECS services composed of tasks and Docker containers and exposes the containers to the user. Fargate has simplified the ECS platform. We will learn how Fargate creates an Elastic Network Interface (ENI) for each task and how auto scaling can be enabled for ECS tasks. You will also learn about using an IAM policy to download Docker images and send logs to CloudWatch. Finally, by the end of this book, you will have learned about how to use ECS CLI to create an ECS cluster and deploy tasks with Docker Compose. What you will learn *Running Docker containers with a managed service *Use Amazon ECS in Fargate launch mode *Configure CloudWatch Logging with Fargate *Use an IAM Role with Fargate *Understand how ECS CLI is used with Fargate *Learn how to use an Application Load Balancer with Fargate *Learn about Auto Scaling with Fargate Who this book is for This book is for Docker users and developers who want to learn about the Fargate platform. Typical job roles for which the book is suitable are DevOps Architect, Docker Engineer, and AWS Cloud Engineer. Prior knowledge of AWS and ECS is helpful but not mandatory.

Understand the Ethereum platform to build distributed applications that are secured and decentralized using blockchain technology Key Features *Build your own decentralized applications using real-world blockchain examples *Implement Ethereum for building smart contracts and cryptocurrency applications with easy-to-follow projects *Enhance your application security with blockchain Book Description Ethereum enables the development of efficient, smart contracts that contain code. These smart contracts can interact with other smart contracts to make decisions, store data, and send Ether to others.Ethereum Projects for Beginners provides you with a clear introduction to creating cryptocurrencies, smart contracts, and decentralized applications. As you make your way through the book, you’ll get to grips with detailed step-by-step processes to build advanced Ethereum projects. Each project will teach you enough about Ethereum to be productive right away. You will learn how tokenization works, think in a decentralized way, and build blockchain-based distributed computing systems. Towards the end of the book, you will develop interesting Ethereum projects such as creating wallets and secure data sharing.By the end of this book, you will be able to tackle blockchain challenges by implementing end-to-end projects using the full power of the Ethereum blockchain. What you will learn *Develop your ideas fast and efficiently using the Ethereum blockchain *Make writing and deploying smart contracts easy and manageable *Work with private data in blockchain applications *Handle large files in blockchain applications *Ensure your decentralized applications are safe *Explore how Ethereum development frameworks work *Create your own cryptocurrency or token on the Ethereum blockchain *Make sure your cryptocurrency is ERC20-compliant to launch an ICO Who this book is for This book is for individuals who want to build decentralized applications using blockchain technology and the power of Ethereum from scratch. Some prior knowledge of JavaScript is required, since most examples use a web frontend.

Make the most of Angular by leveraging design patterns and best practices to build stable and high performing apps Key Features *Get to grips with the benefits and applicability of using different design patterns in Angular with the help of real-world examples *Identify and prevent common problems, programming errors, and anti-patterns *Packed with easy-to-follow examples that can be used to create reusable code and extensible designs Book Description This book is an insightful journey through the most valuable design patterns, and it will provide clear guidance on how to use them effectively in Angular. You will explore some of the best ways to work with Angular and how to use it to meet the stability and performance required in today's web development world. You’ll get to know some Angular best practices to improve your productivity and the code base of your application. We will take you on a journey through Angular designs for the real world, using a combination of case studies, design patterns to follow, and anti-patterns to avoid. By the end of the book, you will understand the various features of Angular, and will be able to apply well-known, industry-proven design patterns in your work. What you will learn *Understand Angular design patterns and anti-patterns *Implement the most useful GoF patterns for Angular *Explore some of the most famous navigational patterns for Angular *Get to know and implement stability patterns *Explore and implement operations patterns *Explore the official best practices for Angular *Monitor and improve the performance of Angular applications Who this book is for If you want to increase your understanding of Angular and apply it to real-life application development, then this book is for you.

Master serverless architectures in Python and their implementation, with Zappa on three different frameworks. Key Features * Scalable serverless Python web services using Django, Flask, and Pyramid. * Learn Asynchronous task execution on AWS Lambda and scheduling using Zappa. * Implementing Zappa in a Docker container. Book Description Serverless applications are becoming very popular these days, not just because they save developers the trouble of managing the servers, but also because they provide several other benefits such as cutting heavy costs and improving the overall performance of the application. This book will help you build serverless applications in a quick and efficient way. We begin with an introduction to AWS and the API gateway, the environment for serverless development, and Zappa. We then look at building, testing, and deploying apps in AWS with three different frameworks--Flask, Django, and Pyramid. Setting up a custom domain along with SSL certificates and configuring them with Zappa is also covered. A few advanced Zappa settings are also covered along with securing Zappa with AWS VPC. By the end of the book you will have mastered using three frameworks to build robust and cost-efficient serverless apps in Python. What you will learn *Build, test, and deploy a simple web service using AWS CLI *Integrate Flask-based Python applications, via AWS CLI configuration *Design Rest APIs integrated with Zappa for Flask and Django *Create a project in the Pyramid framework and configure it with Zappa *Generate SSL Certificates using Amazon Certificate Manager *Configure custom domains with AWS Route 53 *Create a Docker container similar to AWS Lambda Who this book is for Python Developers who are interested in learning how to develop fast and highly scalable serverless applications in Python, will find this book useful

Learn the fundamentals of Java EE 8 APIs to build effective web services Key Features *Design modern and stylish web services with Java EE APIs *Secure your web services with JSON Web Tokens *Explore the advanced concepts of RESTful web services and the JAX-RS API Book Description Java Enterprise Edition is one of the leading application programming platforms for enterprise Java development. With Java EE 8 finally released and the first application servers now available, it is time to take a closer look at how to develop modern and lightweight web services with the latest API additions and improvements. Building RESTful Web Services with Java EE 8 is a comprehensive guide that will show you how to develop state-of-the-art RESTful web services with the latest Java EE 8 APIs. You will begin with an overview of Java EE 8 and the latest API additions and improvements. You will then delve into the details of implementing synchronous RESTful web services and clients with JAX-RS. Next up, you will learn about the specifics of data binding and content marshalling using the JSON-B 1.0 and JSON-P 1.1 APIs. This book also guides you in leveraging the power of asynchronous APIs on the server and client side, and you will learn to use server-sent events (SSEs) for push communication. The final section covers advanced web service topics such as validation, JWT security, and diagnosability. By the end of this book, you will have implemented several working web services and have a thorough understanding of the Java EE 8 APIs required for lightweight web service development. What you will learn *Dive into the latest Java EE 8 APIs relevant for developing web services *Use the new JSON-B APIs for easy data binding *Understand how JSON-P API can be used for flexible processing *Implement synchronous and asynchronous JAX-RS clients *Use server-sent events to implement server-side code *Secure Java EE 8 web services with JSON Web Tokens Who this book is for If you're a Java developer who wants to learn how to implement web services using the latest Java EE 8 APIs, this book is for you. Though no prior knowledge of Java EE 8 is required, experience with a previous Java EE version will be beneficial.

Architect and design data-intensive applications and, in the process, learn how to collect, process, store, govern, and expose data for a variety of use cases Key Features *Integrate the data-intensive approach into your application architecture *Create a robust application layout with effective messaging and data querying architecture *Enable smooth data flow and make the data of your application intensive and fast Book Description Are you an architect or a developer who looks at your own applications gingerly while browsing through Facebook and applauding it silently for its data-intensive, yet ?uent and efficient, behaviour? This book is your gateway to build smart data-intensive systems by incorporating the core data-intensive architectural principles, patterns, and techniques directly into your application architecture. This book starts by taking you through the primary design challenges involved with architecting data-intensive applications. You will learn how to implement data curation and data dissemination, depending on the volume of your data. You will then implement your application architecture one step at a time. You will get to grips with implementing the correct message delivery protocols and creating a data layer that doesn’t fail when running high traffic. This book will show you how you can divide your application into layers, each of which adheres to the single responsibility principle. By the end of this book, you will learn to streamline your thoughts and make the right choice in terms of technologies and architectural principles based on the problem at hand. What you will learn *Understand how to envision a data-intensive system *Identify and compare the non-functional requirements of a data collection component *Understand patterns involving data processing, as well as technologies that help to speed up the development of data processing systems *Understand how to implement Data Governance policies at design time using various Open Source Tools *Recognize the anti-patterns to avoid while designing a data store for applications *Understand the different data dissemination technologies available to query the data in an efficient manner *Implement a simple data governance policy that can be extended using Apache Falcon Who this book is for This book is for developers and data architects who have to code, test, deploy, and/or maintain large-scale, high data volume applications. It is also useful for system architects who need to understand various non-functional aspects revolving around Data Intensive Systems.

Implement intelligent agents using PyTorch to solve classic AI problems, play console games like Atari, and perform tasks such as autonomous driving using the CARLA driving simulator Key Features *Explore the OpenAI Gym toolkit and interface to use over 700 learning tasks *Implement agents to solve simple to complex AI problems *Study learning environments and discover how to create your own Book Description Many real-world problems can be broken down into tasks that require a series of decisions to be made or actions to be taken. The ability to solve such tasks without a machine being programmed requires a machine to be artificially intelligent and capable of learning to adapt. This book is an easy-to-follow guide to implementing learning algorithms for machine software agents in order to solve discrete or continuous sequential decision making and control tasks. Hands-On Intelligent Agents with OpenAI Gym takes you through the process of building intelligent agent algorithms using deep reinforcement learning starting from the implementation of the building blocks for configuring, training, logging, visualizing, testing, and monitoring the agent. You will walk through the process of building intelligent agents from scratch to perform a variety of tasks. In the closing chapters, the book provides an overview of the latest learning environments and learning algorithms, along with pointers to more resources that will help you take your deep reinforcement learning skills to the next level. What you will learn *Explore intelligent agents and learning environments *Understand the basics of RL and deep RL *Get started with OpenAI Gym and PyTorch for deep reinforcement learning *Discover deep Q learning agents to solve discrete optimal control tasks *Create custom learning environments for real-world problems *Apply a deep actor-critic agent to drive a car autonomously in CARLA *Use the latest learning environments and algorithms to upgrade your intelligent agent development skills Who this book is for If you’re a student, game/machine learning developer, or AI enthusiast looking to get started with building intelligent agents and algorithms to solve a variety of problems with the OpenAI Gym interface, this book is for you. You will also find this book useful if you want to learn how to build deep reinforcement learning-based agents to solve problems in your domain of interest. Though the book covers all the basic concepts that you need to know, some working knowledge of Python programming language will help you get the most out of it.

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.

Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity About This Book ? Learn how to apply core machine learning concepts to your games with Unity ? Learn the Fundamentals of Reinforcement Learning and Q-Learning and apply them to your games ? Learn How to build multiple asynchronous agents and run them in a training scenario Who This Book Is For This book is intended for developers with an interest in using Machine learning algorithms to develop better games and simulations with Unity. The reader will be required to have a working knowledge of C# and a basic understanding of Python. What You Will Learn ? Develop Reinforcement and Deep Reinforcement Learning for games. ? Understand complex and advanced concepts of reinforcement learning and neural networks ? Explore various training strategies for cooperative and competitive agent development ? Adapt the basic script components of Academy, Agent, and Brain to be used with Q Learning. ? Enhance the Q Learning model with improved training strategies such as Greedy-Epsilon exploration ? Implement a simple NN with Keras and use it as an external brain in Unity ? Understand how to add LTSM blocks to an existing DQN ? Build multiple asynchronous agents and run them in a training scenario In Detail Unity Machine Learning agents allow researchers and developers to create games and simulations using the Unity Editor, which serves as an environment where intelligent agents can be trained with machine learning methods through a simple-to-use Python API. This book takes you from the basics of Reinforcement and Q Learning to building Deep Recurrent Q-Network agents that cooperate or compete in a multi-agent ecosystem. You will start with the basics of Reinforcement Learning and how to apply it to problems. Then you will learn how to build self-learning advanced neural networks with Python and Keras/TensorFlow. From there you move o n to more advanced training scenarios where you will learn further innovative ways to train your network with A3C, imitation, and curriculum learning models. By the end of the book, you will have learned how to build more complex environments by building a cooperative and competitive multi-agent ecosystem. Style and approach This book focuses on the foundations of ML, RL and DL for building agents in a game or simulation

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.

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.

Enhance your skills in expert module development, deployment, security, DevOps, and cloud Key Features *A step-by-step guide to get you started with PowerShell Core 6.0 *Harness the capabilities of PowerShell Core 6.0 to perform simple to complex administration tasks *Learn core administrative concepts such as scripting, pipelines, and DSC Book Description Beginning with an overview of the different versions of PowerShell, Learn PowerShell Core 6.0 introduces you to VSCode and then dives into helping you understand the basic techniques in PowerShell scripting. You will cover advanced coding techniques, learn how to write reusable code as well as store and load data with PowerShell. This book will help you understand PowerShell security and Just Enough Administration, enabling you to create your own PowerShell repository. The last set of chapters will guide you in setting up, configuring, and working with Release Pipelines in VSCode and VSTS, and help you understand PowerShell DSC. In addition to this, you will learn how to use PowerShell with Windows, Azure, Microsoft Online Services, SCCM, and SQL Server. The final chapter will provide you with some use cases and pro tips. By the end of this book, you will be able to create professional reusable code using security insight and knowledge of working with PowerShell Core 6.0 and its most important capabilities. What you will learn *Get to grips with Powershell Core 6.0 *Explore basic and advanced PowerShell scripting techniques *Get to grips with Windows PowerShell Security *Work with centralization and DevOps with PowerShell *Implement PowerShell in your organization through real-life examples *Learn to create GUIs and use DSC in production Who this book is for If you are a Windows administrator or a DevOps user who wants to leverage PowerShell to automate simple to complex tasks, then this book is for you. Whether you know nothing about PowerShell or just enough to get by, this guide will give you what you need to go to take your scripting to the next level. You’ll also find this book useful if you’re a PowerShell expert looking to expand your knowledge in areas such as PowerShell Security and DevOps.