Deliver great business value by adopting the virtualization platform VMware vSphere 6.5, from the design to the deployment About This Book ? This new edition is based on vSphere 6.5 and has described new features in different areas, including management, security, scalability, availability and so on. ? Design, deploy and manage VMware datacenters ? Implement monitoring and security of VMware workloads with ease. Who This Book Is For If you are an administrator, infrastructure engineer, IT architect, or an IT consultant and analyst who has basic knowledge of VMware vSphere and now wants to master it, then this book is for you. What You Will Learn ? Get a deep understanding of vSphere 6.5 functionalities ? Design and plan a virtualization environment based on vSphere 6.5 ? Manage and administer a vSphere 6.5 environment and resources ? Get tips for the VCP6-DCV and VCIX6-DCV exams (along with use of the vSphere 6 documentation) ? Implement different migration techniques to move your workload across different environments. ? Save your configuration, data and workload from your virtual infrastructure. In Detail VMware vSphere 6.5 provides a powerful, flexible and secure foundation for next-generation applications which helps you create an effective digital transformation. This book will be based on VMware vSphere 6.5 which empowers you to virtualize any complex application with ease. You’ll begin by getting an overview of all the products, solutions and features of the vSphere 6.5 suite, comparing the evolutions with the previous releases. Next ,you’ll design and plan a virtualization infrastructure to drive planning and performance analysis. Following this , you will be proceeding with workflow and installation of components. New network trends are also covered which will help you in optimally designing the vSphere environment. You will also learn the practices and procedures involved in configuring and managing virtual machines in a vSphere infrastructure. With vSphere 6.5, you’ll make use of significantly more powerful capabilities for patching, upgrading, and managing the configuration of the virtual environment. Next we’ll focus on specific availability and resiliency solutions in vSphere. Towards the end of the book you will get information on how to save your configuration, data and workload from your virtual infrastructure. By the end of the book you’ll learn about VMware vSphere 6.5 right from design to deployment and management. Style and Approach This book acts as a reference guide providing real-world scenarios and a possible baseline for each virtualization project based on VMware vSphere.

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks. What you will learn ?Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm ?Fine-tune a neural network to improve the quality of results ?Use deep learning for image and audio processing ?Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases ?Identify problems

"Key Features ?Get to the grips with the latest version of Apache Spark ?Utilize Spark's machine learning library to implement predictive analytics ?Leverage Spark's powerful tools to load, analyze, clean, and transform your data Book De*ion Spark ML is the machine learning module of Spark. It uses in-memory RDDs to process machine learning models faster for clustering, classification, and regression. This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. What you will learn ?Get hands-on with the latest version of Spark ML ?Create your first Spark program with Scala and Python ?Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 ?Access public machine learning datasets and use Spark to load, process, clean, and transform data ?Use Spark's machine learning library to implement programs by utilizing well-known machine learning models ?Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models ?Write Spark functions to evaluate the performance of your machine learning models "

Writing concurrent and parallel programming applications is an integral skill for any Java programmer. Java 9 comes with a host of fantastic features, including significant performance improvements and new APIs. This book will take you through all the new APIs, showing you how to build parallel and multi-threaded applications. The book covers all the elements of the Java Concurrency API, with essential recipes that will help you take advantage of the exciting new capabilities. You will learn how to use parallel and reactive streams to process massive data sets. Next, you will move on to create streams and use all their intermediate and terminal operations to process big collections of data in a parallel and functional way. Further, you ll discover a whole range of recipes for almost everything, such as thread management, synchronization, executors, parallel and reactive streams, and many more. At the end of the book, you will learn how to obtain information about the status of some of the most useful components of the Java Concurrency API and how to test concurrent applications using different tools. What you will learn ?Find out to manage the basic components of the Java Concurrency API ?Use synchronization mechanisms to avoid data race conditions and other problems of concurrent applications ?Separate the thread management from the rest of the application with the Executor framework ?Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework ?Process massive data sets in an optimized way using streams and reactive streams ?See which data structures we can use in concurrent applications and how to use them ?Practice efficient techniques to test concurrent applications ?Get to know tips and tricks to design concurrent applications

Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. What you will learn ?Get a solid understanding of the data processing toolbox available in Java ?Explore the data science ecosystem available in Java

Work through recipes to unlock the full potential of the next generation graphics API―Vulkan About This Book ?This book explores a wide range of modern graphics programming techniques and GPU compute methods to make the best use of the Vulkan API ?Learn techniques that can be applied to a wide range of platforms desktop, smartphones, and embedded devices Who This Book Is For This book is ideal for developers who know C/C++ languages, have some basic familiarity with graphics programming, and now want to take advantage of the new Vulkan API in the process of building next generation computer graphics. Some basic familiarity of Vulkan would be useful to follow the recipes. OpenGL developers who want to take advantage of the Vulkan API will also find this book useful. What You Will Learn?Work with Swapchain to present images on screen ?Create, submit, and synchronize operations processed by the hardware ?Create buffers and images, manage their memory, and upload data to them from CPU ?Explore de*or sets and set up an interface between application and shaders ?Organize drawing operations into a set of render passes and subpasses ?Prepare graphics pipelines to draw 3D scenes and compute pipelines to perform mathematical calculations ?Implement geometry projection and tessellation, texturing, lighting, and post-processing techniques ?Write shaders in GLSL and convert them into SPIR-V assemblies ?Find out about and

Spatial statistics has the potential to provide insight that is not otherwise available through traditional GIS tools. This book is designed to introduce you to the use of spatial statistics so you can solve complex geographic analysis. The book begins by introducing you to the many spatial statistics tools available in ArcGIS. You will learn how to analyze patterns, map clusters, and model spatial relationships with these tools. Further on, you will explore how to extend the spatial statistics tools currently available in ArcGIS, and use the R programming language to create custom tools in ArcGIS through the ArcGIS Bridge using real-world examples. At the end of the book, you will be presented with two exciting case studies where you will be able to practically apply all your learning to analyze and gain insights into real estate data. What you will learn ?Get to know how to measure geographic distributions ?Perform clustering analysis including hot spot and outlier analysis ?Conduct data conversion tasks using the Utilities toolset ?Understand how to use the tools provided by the Mapping Clusters toolset in the Spatial Statistics Toolbox ?Get to grips with the basics of R for performing spatial statistical programming ?Create custom ArcGIS tools with R and ArcGIS Bridge ?Understand the application of Spatial Statistics tools

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This Book ?Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow ?Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide ?Real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn ?Learn about machine learning landscapes along with the historical development and progress of deep learning ?Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x ?Access public datasets and utilize them using TensorFlow to load, process, and transform data ?Use TensorFlow on real-world datasets, including images, text, and more ?Learn how to evaluate the performance of your deep learning models ?Using deep learning for scalable object detection and mobile computing ?Train machines quickly to learn from data by exploring reinforcement learning techniques ?Explore active areas of deep learning research and applications

Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecma* 6 and Type*

If you already know some HTML and CSS and understand the principles of responsive web design, this book is for you. There's something here for you to learn regardless of whether you're a web designer or web developer, or whether you're a seasoned expert web professional.

You've started down the path of jQuery Mobile, now begin mastering some of jQuery Mobile's higher level topics. Go beyond jQuery Mobile's documentation and master one of the hottest mobile technologies out there. Previous JavaScript and PHP experience can help you get the most out of this book.

The book is aimed at Java developers who wish to develop Java EE applications while taking advantage of NetBeans functionality to automate repetitive tasks. Familiarity with NetBeans or Java EE is not assumed.

This book is for all the software and web engineers wanting to apply the promises paradigm to their next project and get the best outcome from it. This book also acts as a reference for the engineers who are already using promises in their projects and want to improve their current knowledge to reach the next level. To get the most benefit from this book, you should know basic programming concepts, have a familiarity with JavaScript, and a good understanding of HTML.

Intended for seasoned Go programmers who want to put their expertise in Go to use to solve big, real-world, modern problems. With a basic understanding of channels and goroutines, you will hone your skills to build tools and programs that are quick and simple. You need not be an expert in distributed systems or technologies in order to deliver solutions capable of great scale. It is assumed that you are familiar with the basic concepts of Go.

This book is ideal for any JavaScript developer who is interested in producing well-tested code. If you have no prior experience with testing, Node.js, or any other tool, do not worry, as they will be explained from scratch.

Mastering Unity Scripting is an advanced book intended for students, educators, and professionals familiar with the Unity basics as well as the basics of *ing. Whether you've been using Unity for a short time or are an experienced user, this book has something important and valuable to offer to help you improve your game development workflow.

If you are a virtualization professional who wants to unleash the power of automation and combat the complexity of sprawling virtual environments, this book is ideal for you. This book will enhance your skills of administering VMware vSphere and vCloud Director with PowerCLI.

If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. Basic knowledge of Python is assumed.

If you are a VMware administrator who is interested in automating your infrastructure, this book is for you. An understanding of basic programming concepts is advised. No previous knowledge of Orchestrator is required, although some previous knowledge of it will allow you to get started more easily.

This book is for developers and data architects who have some exposure to databases. It is assumed that you understand the basic concepts of tables and common database objects, including privileges and security.

This book is for anyone who wants to have a go at creating commercially successfully games for Android and iOS. You don’t need game development or programming experience.