Learn the importance of architectural and design patterns in producing and sustaining next-generation IT and business-critical applications with this guide. About This Book ? Use patterns to tackle communication, integration, application structure, and more ? Implement modern design patterns such as microservices to build resilient and highly available applications ? Choose between the MVP, MVC, and MVVM patterns depending on the application being built Who This Book Is For This book will empower and enrich IT architects (such as enterprise architects, software product architects, and solution and system architects), technical consultants, evangelists, and experts. What You Will Learn ? Understand how several architectural and design patterns work to systematically develop multitier web, mobile, embedded, and cloud applications ? Learn object-oriented and component-based software engineering principles and patterns ? Explore the frameworks corresponding to various architectural patterns ? Implement domain-driven, test-driven, and behavior-driven methodologies ? Deploy key platforms and tools effectively to enable EA design and solutioning ? Implement various patterns designed for the cloud paradigm In Detail Enterprise Architecture (EA) is typically an aggregate of the business, application, data, and infrastructure architectures of any forward-looking enterprise. Due to constant changes and rising complexities in the business and technology landscapes, producing sophisticated architectures is on the rise. Architectural patterns are gaining a lot of attention these days. The book is divided in three modules. You'll learn about the patterns associated with object-oriented, component-based, client-server, and cloud architectures. The second module covers Enterprise Application Integration (EAI) patterns and how they are architected using various tools and patterns. You will come across patterns for Service-Oriented Architecture (SOA), Event-Driven Architecture (EDA), Resource-Oriented Architecture (ROA), big data analytics architecture, and Microservices Architecture (MSA). The final module talks about advanced topics such as Docker containers, high performance, and reliable application architectures. The key takeaways include understanding what architectures are, why they're used, and how and where architecture, design, and integration patterns are being leveraged to build better and bigger systems. Style and Approach This book adopts a hands-on approach with real-world examples and use cases.

Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery About This Book ? Get comfortable using pandas and Python as an effective data exploration and analysis tool ? Explore pandas through a framework of data analysis, with an explanation of how pandas is well suited for the various stages in a data analysis process ? A comprehensive guide to pandas with many of clear and practical examples to help you get up and using pandas Who This Book Is For This book is ideal for data scientists, data analysts, Python programmers who want to plunge into data analysis using pandas, and anyone with a curiosity about analyzing data. Some knowledge of statistics and programming will be helpful to get the most out of this book but not strictly required. Prior exposure to pandas is also not required. What You Will Learn ? Understand how data analysts and scientists think about of the processes of gathering and understanding data ? Learn how pandas can be used to support the end-to-end process of data analysis ? Use pandas Series and DataFrame objects to represent single and multivariate data ? Slicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sources ? How to access data from external sources such as files, databases, and web services ? Represent and manipulate time-series data and the many of the intricacies involved with this type of data ? How to visualize statistical information ? How to use pandas to solve several common data representation and analysis problems within finance In Detail You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance. With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science. Style and approach ? Step-by-step instruction on using pandas within an end-to-end framework of performing data analysis ? Practical demonstration of using Python and pandas using interactive and incremental examples

Over 100 recipes to help you overcome your difficulties with C++ programming and gain a deeper understanding of the working of modern C++ About This Book ? Explore the most important language and library features of C++17, including containers, algorithms, regular expressions, threads, and more, ? Get going with unit testing frameworks Boost.Test, Google Test and Catch, ? Extend your C++ knowledge and take your development skills to new heights by making your applications fast, robust, and scalable. Who This Book Is For If you want to overcome difficult phases of development with C++ and leverage its features using modern programming practices, then this book is for you. The book is designed for both experienced C++ programmers as well as people with strong knowledge of OOP concepts. What You Will Learn ? Get to know about the new core language features and the problems they were intended to solve ? Understand the standard support for threading and concurrency and know how to put them on work for daily basic tasks ? Leverage C++’s features to get increased robustness and performance ? Explore the widely-used testing frameworks for C++ and implement various useful patterns and idioms ? Work with various types of strings and look at the various aspects of compilation ? Explore functions and callable objects with a focus on modern features ? Leverage the standard library and work with containers, algorithms, and iterators ? Use regular expressions for find and replace string operations ? Take advantage of the new filesystem library to work with files and directories ? Use the new utility additions to the standard library to solve common problems developers encounter including string_view, any , optional and variant types In Detail C++ is one of the most widely used programming languages. Fast, efficient, and flexible, it is used to solve many problems. The latest versions of C++ have seen programmers change the way they code, giving up on the old-fashioned C-style programming and adopting modern C++ instead. Beginning with the modern language features, each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. You will learn major concepts about the core programming language as well as common tasks faced while building a wide variety of software. You will learn about concepts such as concurrency, performance, meta-programming, lambda expressions, regular expressions, testing, and many more in the form of recipes. These recipes will ensure you can make your applications robust and fast. By the end of the book, you will understand the newer aspects of C++11/14/17 and will be able to overcome tasks that are time-consuming or would break your stride while developing. Style and approach This book follows a recipe-based approach, with examples that will empower you to implement the core programming language features and explore the newer aspects of C++.

Explore over 110 recipes to analyze data and build predictive models with simple and easy-to-use R code About This Book ? Apply R to simplify predictive modeling with short and simple code ? Use machine learning to solve problems ranging from small to big data ? Build a training and testing dataset, applying different classification methods. Who This Book Is For This book is for data science professionals, data analysts, or people who have used R for data analysis and machine learning who now wish to become the go-to person for machine learning with R. Those who wish to improve the efficiency of their machine learning models and need to work with different kinds of data set will find this book very insightful. What You Will Learn ? Create and inspect transaction datasets and perform association analysis with the Apriori algorithm ? Visualize patterns and associations using a range of graphs and find frequent item-sets using the Eclat algorithm ? Compare differences between each regression method to discover how they solve problems ? Detect and impute missing values in air quality data ? Predict possible churn users with the classification approach ? Plot the autocorrelation function with time series analysis ? Use the Cox proportional hazards model for survival analysis ? Implement the clustering method to segment customer data ? Compress images with the dimension reduction method ? Incorporate R and Hadoop to solve machine learning problems on big data In Detail Big data has become a popular buzzword across many industries. An increasing number of people have been exposed to the term and are looking at how to leverage big data in their own businesses, to improve sales and profitability. However, collecting, aggregating, and visualizing data is just one part of the equation. Being able to extract useful information from data is another task, and a much more challenging one. Machine Learning with R Cookbook, Second Edition uses a practical approach to teach you how to perform machine learning with R. Each chapter is divided into several simple recipes. Through the step-by-step instructions provided in each recipe, you will be able to construct a predictive model by using a variety of machine learning packages. In this book, you will first learn to set up the R environment and use simple R commands to explore data. The next topic covers how to perform statistical analysis with machine learning analysis and assess created models, covered in detail later on in the book. You'll also learn how to integrate R and Hadoop to create a big data analysis platform. The detailed illustrations provide all the information required to start applying machine learning to individual projects. With Machine Learning with R Cookbook, machine learning has never been easier. Style and approach This is an easy-to-follow guide packed with hands-on examples of machine learning tasks. Each topic includes step-by-step instructions on tackling difficulties faced when applying R to machine learning.

Master realistic animations and graphics, particle systems, game AI and physics, sprites and VR development with Unity 2017 About This Book ? Create professional grade games with realistic animation and graphics, particle systems and game physics with Unity 2017 ? Unleash the power of C# *ing to create intelligent game AI and professional grade game workflows. ? Create immersive VR games using the latest Unity 2017 VR SDK. Who This Book Is For If you are a Unity developer who now wants to develop and deploy interesting games by leveraging the new features of Unity 2017, then this is the book for you. Basic knowledge of C# programming is assumed. What You Will Learn ? Explore hands-on tasks and real-world scenarios to make a Unity horror adventure game ? Create enemy characters that act intelligently and make reasoned decisions ? Use data files to save and restore game data in a way that is platform-agnostic ? Get started with VR development ? Use navigation meshes, occlusion culling, and Profiler tools ? Work confidently with GameObjects, rotations, and transformations ? Understand specific gameplay features such as AI enemies, inventory systems, and level design In Detail Do you want to make the leap from being an everyday Unity developer to being a pro game developer? Then look no further! This book is your one-stop solution to creating mesmerizing games with lifelike features and amazing gameplay. This book focuses in some detail on a practical project with Unity, building a first-person game with many features. You'll delve into the architecture of a Unity game, creating expansive worlds, interesting render effects, and other features to make your games special. You will create individual game components, use efficient animation techniques, and implement collision and physics effectively. Specifically, we'll explore optimal techniques for importing game assets, such as meshes and textures; tips and tricks for effective level design; how to animate and * NPCs; how to configure and deploy to mobile devices; how to prepare for VR development; how to work with version control; and more. By the end of this book, you'll have developed sufficient competency in Unity development to produce fun games with confidence. Style and approach This book takes an easy-to-follow, step-by-step tutorial approach. You will create an advanced level Unity game with an emphasis on leveraging advanced Unity 2017 features while developing the game in its entirety.

Find out how to craft effective, business-oriented Java EE 8 applications that target customer’s demands in the age of Cloud platforms and container technology. About This Book ? Understand the principles of modern Java EE and how to realize effective architectures ? Gain knowledge of how to design enterprise software in the age of automation, Continuous Delivery and Cloud platforms ? Learn about the reasoning and motivations behind state-of-the-art enterprise Java technology, that focuses on business Who This Book Is For This book is for experienced Java EE developers who are aspiring to become the architects of enterprise-grade applications, or software architects who would like to leverage Java EE to create effective blueprints of applications. What You Will Learn ? What enterprise software engineers should focus on ? Implement applications, packages, and components in a modern way ? Design and structure application architectures ? Discover how to realize technical and cross-cutting aspects ? Get to grips with containers and container orchestration technology ? Realize zero-dependency, 12-factor, and Cloud-native applications ? Implement automated, fast, reliable, and maintainable software tests ? Discover distributed system architectures and their requirements In Detail Java EE 8 brings with it a load of features, mainly targeting newer architectures such as microservices, modernized security APIs, and cloud deployments. This book will teach you to design and develop modern, business-oriented applications using Java EE 8. It shows how to structure systems and applications, and how design patterns and Domain Driven Design aspects are realized in the age of Java EE 8. You will learn about the concepts and principles behind Java EE applications, and how to effect communication, persistence, technical and cross-cutting concerns, and asynchronous behavior. This book covers Continuous Delivery, DevOps, infrastructure-as-code, containers, container orchestration technologies, such as Docker and Kubernetes, and why and especially how Java EE fits into this world. It also covers the requirements behind containerized, zero-dependency applications and how modern Java EE application servers support these approaches. You will also learn about automated, fast, and reliable software tests, in different test levels, scopes, and test technologies. This book covers the prerequisites and challenges of distributed systems that lead to microservice, shared-nothing architectures. The challenges and solutions of consistency versus scalability will further lead us to event sourcing, event-driven architectures, and the CQRS principle. This book also includes the nuts and bolts of application performance as well as how to realize resilience, logging, monitoring and tracing in a modern enterprise world. Last but not least the demands of securing enterprise systems are covered. By the end, you will understand the ins and outs of Java EE so that you can make critical design decisions that not only live up to, but also surpass your clients' expectations. Style and approach This book focuses on solving business problems and meeting customer demands in the enterprise world. It covers how to create enterprise applications with reasonable technology choices, free of cargo-cult and over-engineering. The aspects shown in this book not only demonstrate how to realize a certain solution, but also explain its motivations and reasoning.

Build exciting AR applications on mobile and wearable devices with Unity 3D, Vuforia, ARToolKit, Microsoft Mixed Reality HoloLens, Apple ARKit, and Google ARCore About This Book ? Create unique AR applications from scratch, from beginning to end, with step-by-step tutorials ? Use Unity 3D to efficiently create AR apps for Android, iOS, and Windows platforms ? Use Vuforia, ARTookKit, Windows Mixed Reality, and Apple ARKit to build AR projects for a variety of markets ? Learn best practices in AR user experience, software design patterns, and 3D graphics Who This Book Is For The ideal target audience for this book is developers who have some experience in mobile development, either Android or iOS. Some broad web development experience would also be beneficial. What You Will Learn ? Build Augmented Reality applications through a step-by-step, tutorial-style project approach ? Use the Unity 3D game engine with the Vuforia AR platform, open source ARToolKit, Microsoft's Mixed Reality Toolkit, Apple ARKit, and Google ARCore, via the C# programming language ? Implement practical demo applications of AR including education, games, business marketing, and industrial training ? Employ a variety of AR recognition modes, including target images, markers, objects, and spatial mapping ? Target a variety of AR devices including phones, tablets, and wearable smartglasses, for Android, iOS, and Windows HoloLens ? Develop expertise with Unity 3D graphics, UIs, physics, and event systems ? Explore and utilize AR best practices and software design patterns In Detail Augmented Reality brings with it a set of challenges that are unseen and unheard of for traditional web and mobile developers. This book is your gateway to Augmented Reality development—not a theoretical showpiece for your bookshelf, but a handbook you will keep by your desk while coding and architecting your first AR app and for years to come. The book opens with an introduction to Augmented Reality, including markets, technologies, and development tools. You will begin by setting up your development machine for Android, iOS, and Windows development, learning the basics of using Unity and the Vuforia AR platform as well as the open source ARToolKit and Microsoft Mixed Reality Toolkit. You will also receive an introduction to Apple's ARKit and Google's ARCore! You will then focus on building AR applications, exploring a variety of recognition targeting methods. You will go through multiple complete projects illustrating key market sectors including business marketing, education, industrial training, and gaming. By the end of the book, you will have gained the necessary knowledge to make quality content appropriate for a range of AR devices, platforms, and intended uses. Style and approach This book adopts a practical, step-by-step, tutorial-style approach. The design principles and methodology will be explained by creating different modules of the AR app.

Explore Implementation of core kernel subsystems About This Book ? Master the design, components, and structures of core kernel subsystems ? Explore kernel programming interfaces and related algorithms under the hood ? Completely updated material for the 4.12.10 kernel Who This Book Is For If you are a kernel programmer with a knowledge of kernel APIs and are looking to build a comprehensive understanding, and eager to explore the implementation, of kernel subsystems, this book is for you. It sets out to unravel the underlying details of kernel APIs and data structures, piercing through the complex kernel layers and gives you the edge you need to take your skills to the next level. What You Will Learn ? Comprehend processes and fles—the core abstraction mechanisms of the Linux kernel that promote effective simplification and dynamism ? Decipher process scheduling and understand effective capacity utilization under general and real-time dispositions ? Simplify and learn more about process communication techniques through signals and IPC mechanisms ? Capture the rudiments of memory by grasping the key concepts and principles of physical and virtual memory management ? Take a sharp and precise look at all the key aspects of interrupt management and the clock subsystem ? Understand concurrent execution on SMP platforms through kernel synchronization and locking techniques In Detail Mastering Linux Kernel Development looks at the Linux kernel, its internal arrangement and design, and various core subsystems, helping you to gain significant understanding of this open source marvel. You will look at how the Linux kernel, which possesses a kind of collective intelligence thanks to its scores of contributors, remains so elegant owing to its great design. This book also looks at all the key kernel code, core data structures, functions, and macros, giving you a comprehensive foundation of the implementation details of the kernel’s core services and mechanisms. You will also look at the Linux kernel as well-designed software, which gives us insights into software design in general that are easily scalable yet fundamentally strong and safe. By the end of this book, you will have considerable understanding of and appreciation for the Linux kernel. Style and approach Each chapter begins with the basic conceptual know-how for a subsystem and extends into the details of its implementation. We use appropriate code excerpts of critical routines and data structures for subsystems.

Implement and manage your software-defined, massively scalable storage system About This Book ? Explore Ceph's architecture in order to achieve scalability and high availability ? Learn to utilize Ceph efficiently with the help of practical examples ? Successfully implement Ceph clusters to scale-out storage solutions along with outstanding data protection Who This Book Is For A basic knowledge of GNU/Linux, and storage systems, and server components is assumed. If you have no experience of software-defined storage solutions and Ceph, but are eager to learn about them, this is the book for you. What You Will Learn ? The limitations of existing systems and why you should use Ceph as a storage solution ? Familiarity with Ceph's architecture, components, and services ? Instant deployment and testing of Ceph within a Vagrant and VirtualBox environment ? Ceph operations including maintenance, monitoring, and troubleshooting ? Storage provisioning of Ceph's block, object, and filesystem services ? Integrate Ceph with OpenStack ? Advanced topics including erasure coding, CRUSH maps, and performance tuning ? Best practices for your Ceph clusters In Detail Learning Ceph, Second Edition will give you all the skills you need to plan, deploy, and effectively manage your Ceph cluster. You will begin with the first module, where you will be introduced to Ceph use cases, its architecture, and core projects. In the next module, you will learn to set up a test cluster, using Ceph clusters and hardware selection. After you have learned to use Ceph clusters, the next module will teach you how to monitor cluster health, improve performance, and troubleshoot any issues that arise. In the last module, you will learn to integrate Ceph with other tools such as OpenStack, Glance, Manila, Swift, and Cinder. By the end of the book you will have learned to use Ceph effectively for your data storage requirements. Style and approach This step-by-step guide, including use cases and examples, not only helps you to easily use Ceph but also demonstrates how you can use it to solve any of your server or drive storage issues.

Learn in easy stages how to rapidly build leading-edge web applications from scratch. About This Book ? Develop powerful web applications rapidly with WordPress ? Explore the significant features and improvements introduced in WordPress 4.7 by learning the numerous tips and techniques in this book. ? Unleash the power of REST API endpoints to make your interaction with websites new and innovative. Who This Book Is For This book is targeted at WordPress developers and designers who want to develop quality web applications within a limited time frame and maximize their profits. A prior knowledge of basic web development and design is assumed. What You Will Learn ? Develop extendable plugins with the use of WordPress features in core modules ? Develop pluggable modules to extend the core features of WordPress as independent modules ? Manage permissions for a wide range of content types in web applications based on different user types ? Follow WordPress coding standards to develop reusable and maintainable code ? Build and customize themes beyond conventional web layouts ? Explore the power of core database tables and understand the limitations when designing database tables for large applications ? Integrate open source modules into WordPress applications to keep up with the latest open source technologies ? Customize the WordPress admin section and themes to create the look and feel of a typical web application In Detail WordPress is one of the most rapidly expanding markets on the Web. Learning how to build complex and scalable web applications will give you the ability and knowledge to step into the future of WordPress. WordPress 4.7 introduces some exciting new improvements and several bug fixes, which further improve the entire development process.This book is a practical, scenario-based guide to expanding the power of the WordPress core modules to develop modular and maintainable real-world applications from scratch. This book consistently emphasizes adapting WordPress features into web applications. It will walk you through the advanced usages of existing features such as access controlling; database handling; custom post types; pluggable plugins; content restrictions; routing; translation; caching; and many more, while you build the backend of a forum management application. This book begins by explaining how to plan the development of a web application using WordPress' core features. Once the core features are explained, you will learn how to build an application by extending them through custom plugin development. Finally, you will explore advanced non-functional features and application integration. After reading this book, you will have the ability to develop powerful web applications rapidly within limited time frames. Style and approach An extensive, practical guide that explains how to adapt WordPress features, both conventional and trending, for web 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*

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

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

"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

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

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

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

Build cloud native applications in Python About This Book ? This is the only reliable resource that showcases the tools and techniques you need build robust and resilient cloud native applications in Python ? Learn how to architect your application on both, the AWS and Azure clouds for high availability ? Assess, monitor, and troubleshoot your applications in the cloud Who This Book Is For This book is ideal for developers with a basic knowledge of Python who want to learn to build, test, and scale their Python-based applications. No prior experience of writing microservices in Python is required. What You Will Learn ? Get to know “the way of the cloud”, including why developing good cloud software is fundamentally about mindset and discipline ? Know what microservices are and how to design them ? Create reactive applications in the cloud with third-party messaging providers ? Build massive-scale, user-friendly GUIs with React and Flux ? Secure cloud-based web applications: the do’s, don’ts, and options ? Plan cloud apps that support continuous delivery and deployment In Detail Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you’ve deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform Style and approach Filled with examples, this book takes a step-by-step approach to teach you each and every configuration you need to make your application highly available and fault tolerant.

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book ? Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. ? Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. ? Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn ? Acquaint yourself with important elements of Machine Learning ? Understand the feature selection and feature engineering process ? Assess performance and error trade-offs for Linear Regression ? Build a data model and understand how it works by using different types of algorithm ? Learn to tune the parameters of Support Vector machines ? Implement clusters to a dataset ? Explore the concept of Natural Processing Language and Recommendation Systems ? Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.

Build a variety of real-world applications by taking advantage of the newest features of Java 9 About This Book ? See some of the new features of Java 9 and be introduced to parts of the Java SDK ? This book provides a set of diverse, interesting projects that range in complexity from fairly simple to advanced and cover HTTP 2.0 ? Take advantage of Java's new modularity features to write real-world applications that solve a variety of problems Who This Book Is For This book is for Java developers who are already familiar with the language. Familiarity with more advanced topics, such as network programming and threads, would be helpful, but is not assumed. What You Will Learn ? Learn how to package Java applications as modules by using the Java Platform Module System ? Implement process management in Java by using the all-new process handling API ? Integrate your applications with third-party services in the cloud ? Interact with mail servers using JavaMail to build an application that filters spam messages ? Learn to use JavaFX to build rich GUI based applications, which are an essential element of application development ? Write microservices in Java using platform libraries and third-party frameworks ? Integrate a Java application with MongoDB to build a cloud-based note taking application In Detail Java is a powerful language that has applications in a wide variety of fields. From playing games on your computer to performing banking transactions, Java is at the heart of everything. The book starts by unveiling the new features of Java 9 and quickly walks you through the building blocks that form the basis of writing applications. There are 10 comprehensive projects in the book that will showcase the various features of Java 9. You will learn to build an email filter that separates spam messages from all your inboxes, a social media aggregator app that will help you efficiently track various feeds, and a microservice for a client/server note application, to name a few. The book covers various libraries and frameworks in these projects, and also introduces a few more frameworks that complement and extend the Java SDK. Through the course of building applications, this book will not only help you get to grips with the various features of Java 9, but will also teach you how to design and prototype professional-grade applications with performance and security considerations. Style and approach This is a learn-as-you-build practical guide to building full-fledged applications using Java 9. With a project-based approach, we’ll improve your Java skills. You will experience a variety of solutions to problems with Java.