Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is For This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book. Style and approach This book follows a tutorial approach, providing examples of each of the major concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.

Master the art of providing effective IT services to your customers by leveraging Zendesk About This Book Deep dive into the functionalities of Zendesk and improve your organization's customer services Learn how to expand the capabilities of Zendesk by integrating and extending it with third-party tools A master level guide that manages tickets, channels, and workflows along with advanced security features Who This Book Is For This book is for proficient Zendesk administrators who want to unlock the full potential of their Zendesk environment by gaining a deeper understanding of Zendesk's advanced customization options. What You Will Learn Customize ticket channels such as Email, Twitter, Facebook, and Web-Widget Add business rules to create a more effective and automated Zendesk environment Use Zendesk apps to add more functionality to the Zendesk setup Extend Zendesk with JIRA and Salesforce Create custom metrics within GoodData in order to set up customized and automated reports Learn how to secure and troubleshoot Zendesk In Detail Zendesk is a cloud-based customer service solution that is widely used because it is easy, efficienct, flexible, and low cost. It is highly scalable and is great for organizations of all sizes. If you're a Zendesk administrator and are looking to explore advanced-level concepts, then this book is for you. It covers the core functionalities such as managing users, groups, and the organization, and creating and adding custom fields. You will learn how to add customized ticket channels to your account. Then, you will focus on customizing business rules and extending Zendesk with JIRA and Salesforce. Towards the end, the book emphasizes security and troubleshooting aspects as well as providing tips and tricks to create a more efficient support environment. By the end of this book, you will be able to turn a basic Zendesk setup into a highly customized working environment. Style and approach This advanced guide provides easy to understand examples to ensure you gain expertise with Zendesk.

Take charge of SaltStack to automate and configure your enterprise-grade environments About This Book Automate tasks effectively and take charge of your infrastructure Effectively scale Salt to manage thousands of machines and tackle everyday problems Explore Salt’s inner workings and advance your knowledge of it Who This Book Is For This book is ideal for IT professionals and ops engineers who already manage groups of servers, but would like to expand their knowledge and gain expertise with SaltStack. This book explains the advanced features and concepts of Salt. A basic knowledge of Salt is required in order to get to grips with advanced Salt features. What You Will Learn Automate tasks effectively, so that your infrastructure can run itself Start building more complex concepts Master user-level internals Build scaling strategies Explore monitoring strategies Learn how to troubleshoot Salt and its subcomponents Explore best practices for Salt In Detail SaltStack is a powerful configuration management and automation suite designed to manage servers and tens of thousands of nodes. This book showcases Salt as a very powerful automation framework. We will review the fundamental concepts to get you in the right frame of mind, and then explore Salt in much greater depth. You will explore Salt SSH as a powerful tool and take Salt Cloud to the next level. Next, you’ll master using Salt services with ease in your infrastructure. You will discover methods and strategies to scale your infrastructure properly. You will also learn how to use Salt as a powerful monitoring tool. By the end of this book, you will have learned troubleshooting tips and best practices to make the entire process of using Salt pain-free and easy. Style and approach This book follows a step-by-step conversational tone. Topics are covered in detail through examples and a user-friendly approach.

Unleash the power and flexibility of the Bayesian framework About This Book Simplify the Bayes process for solving complex statistical problems using Python; Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems and practice exercises; Learn how and when to use Bayesian analysis in your applications with this guide. Who This Book Is For Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to day projects. Programming experience with Python is essential. No previous statistical knowledge is assumed. What You Will Learn Understand the essentials Bayesian concepts from a practical point of view Learn how to build probabilistic models using the Python library PyMC3 Acquire the skills to sanity-check your models and modify them if necessary Add structure to your models and get the advantages of hierarchical models Find out how different models can be used to answer different data analysis questions When in doubt, learn to choose between alternative models. Predict continuous target outcomes using regression analysis or assign classes using logistic and softmax regression. Learn how to think probabilistically and unleash the power and flexibility of the Bayesian framework In Detail The purpose of this book is to teach the main concepts of Bayesian data analysis. We will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, we will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. We will also look into mixture models and clustering data, and we will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems. Style and approach Bayes algorithms are widely used in statistics, machine learning, artificial intelligence, and data mining. This will be a practical guide allowing the readers to use Bayesian methods for statistical modelling and analysis using Python.

Get up to date with the finer points of Ubuntu Server using this comprehensive guide About This Book Get well-versed with newly-added features in Ubuntu 16.04 Master the art of installing, managing, and troubleshooting Ubuntu Server A practical easy-to-understand book that will help you enhance your existing skills. Who This Book Is For This book is intended for readers with intermediate or advanced-beginner skills with Linux, who would like to learn all about setting up servers with Ubuntu Server. This book assumes that the reader knows the basics of Linux, such as editing configuration files and running basic commands. What You Will Learn Learn how to manage users, groups, and permissions Encrypt and decrypt disks with Linux Unified Key Setup /Luks Setup SSH for remote access, and connect it to other nodes Understand how to add, remove, and search for packages Use NFS and Samba to share directories with other users Get to know techniques for managing Apache and MariaDB Explore best practices and troubleshooting techniques In Detail Ubuntu is a Debian-based Linux operating system, and has various versions targeted at servers, desktops, phones, tablets and televisions. The Ubuntu Server Edition, also called Ubuntu Server, offers support for several common configurations, and also simplifies common Linux server deployment processes. With this book as their guide, readers will be able to configure and deploy Ubuntu Servers using Ubuntu Server 16.04, with all the skills necessary to manage real servers. The book begins with the concept of user management, group management, as well as file-system permissions. To manage your storage on Ubuntu Server systems, you will learn how to add and format storage and view disk usage. Later, you will also learn how to configure network interfaces, manage IP addresses, deploy Network Manager in order to connect to networks, and manage network interfaces. Furthermore, you will understand how to start and stop services so that you can manage running processes on Linux servers. The book will then demonstrate how to access and share files to or from Ubuntu Servers. You will learn how to create and manage databases using MariaDB and share web content with Apache. To virtualize hosts and applications, you will be shown how to set up KVM/Qemu and Docker and manage virtual machines with virt-manager. Lastly, you will explore best practices and troubleshooting techniques when working with Ubuntu Servers. By the end of the book, you will be an expert Ubuntu Server user well-versed in its advanced concepts. Style and Approach This book is an advanced guide that will show readers how to administer, manage, and deploy Ubuntu server and will also provide expert-level knowledge on advanced security and backup techniques.

Quick fixes to your common C# programming problems, with a focus on C# 6.0 About This Book Unique recipes for C#, that places it in its real-world context. You will be able to get yourself out of any coding-corner youve backed yourself into. All code samples available through GitHub to bring C#. In line with modern development workflows, written to the latest specification of C# 6.0. Who This Book Is For The book is aimed at developers who have basic familiarity with C# programming and will know the VS 2015 environment. What You Will Learn Write better and less code to achieve the same result as in previous versions of C#. Generate tests from the Code Contracts for mission critical methods. Integrate code in Visual Studio with GitHub. Create a web application in Azure. Design and build a microservice architecture Demystify the Rx library using Reactive extensions Write high performing codes in C# and understanding multi-threading. Security and Debugging. Implement Code Contracts on code in Visual Studio. In Detail During your application development workflow, there is always a moment when you need to get out of a tight spot. Through a recipe-based approach, this book will help you overcome common programming problems and get your applications ready to face the modern world. We start with C# 6, giving you hands-on experience with the new language features. Next, we work through the tasks that you perform on a daily basis such as working with strings, generics, and lots more. Gradually, we move on to more advanced topics such as the concept of object-oriented programming, asynchronous programming, reactive extensions, and code contracts. You will learn responsive high performance programming in C# and how to create applications with Azure. Next, we will review the choices available when choosing a source control solution. At the end of the book, we will show you how to create secure and robust code, and will help you ramp up your skills when using the new version of C# 6 and Visual Studio Style and Approach Unique recipe-based guide that will help you gain a solid understanding of the new concepts in C# 6 and Visual Studio Enterprise 2015 in a concise and technically correct manner.

An in-depth guide to configuring NGINX for your everyday server needs About This Book Get tips, tricks, and master insight to help you configure NGINX for any server situation Integrate NGINX into your applications architecture with is, using hands-on guidance and practical code samples that are free to use Troubleshoot configuration problems before and as they arise, for a seamless NGINX server experience Who This Book Is For This book is for system administrators and engineers who want to personalize NGINX, and design a robust configuration module to solve their hosting problems. Some knowledge of NGINX is a plus, but is not a prerequisite. What You Will Learn Compile the right third-party module to meet your needs Write an authentication server to use with the mail proxy module Create your own SSL certificates to encrypt connections Use try_files to solve your file-existence check problems Cache and compress responses to get speedier user interaction Integrate popular PHP frameworks with the FastCGI module Construct useful logging configurations In Detail NGINX is a high-performance HTTP server and mail proxy designed to use very few system resources. But despite its power it is often a challenge to properly configure NGINX to meet your expectations. Mastering Nginx is the solution – an insider’s guide that will clarify the murky waters of NGINX’s configuration. Tune NGINX for various situations, improve your NGINX experience with some of the more obscure configuration directives, and discover how to design and personalize a configuration to match your needs. To begin with, quickly brush up on installing and setting up the NGINX server on the OS and its integration with third-party modules. From here, move on to explain NGINX's mail proxy module and its authentication, and reverse proxy to solve scaling issues. Then see how to integrate NGINX with your applications to perform tasks. The latter part of the book focuses on working through techniques to solve common web issues and the know-hows using NGINX modules. Finally, we will also explore different configurations that will help you troubleshoot NGINX server and assist with performance tuning. Style and approach This is a mastering guide where you will follow an instructional, conversational approach working through problems and their solutions.

An example-based practical guide to get you up and running with Unreal Engine 4.X About This Book A unique resource on Unreal with an interactive example based approach that is sure to get you up and running immediately Will feature four unique game projects that increase in complexity which will enable readers to build their game development skills using Unreal Engine 4 and the C++ programming language Will be the most up to date book in the market on Unreal with full coverage of the new features of UE4 Who This Book Is For Unreal Engine 4.X by Example was written for keen developers who wish to learn how to fully utilise Unreal Engine 4 to make awesome and engrossing game titles. Whether you are brand new to game development or a seasoned expert, you will be able to make use of the engine with C++. Experience with both C++ and other game engines is preferred before embarking on the Unreal by Example journey, but with a little external research into the basics of C++ programming, this book can take a complete game development novice to an Unreal Engine Developer! What You Will Learn Use C++ with Unreal Engine to boost the development potential of any Unreal Engine project Vastly improve workflow and content creation with the visual *ing system blueprint Design, test, and implement interesting game worlds using Unreal Engines built-in editor Build a networked, feature-rich first person shooter that you can play with others over LAN Build design-centric game worlds that play to needs of your game ideas Paint your game worlds via the creation and modification of visual shaders called materials Gain knowledge of other game development disciplines through the use of the Animation and Material tool sets Create feature-rich game projects with a sophisticated visual quality and feature set In Detail With Unreal Engine 4 being made free to use, for any keen game developer it is quickly becoming the most popular game engine in today’s development industry. The engine offers a rich feature set that can be customized and built upon through the use of C++. This book will cover how to work with Unreal Engine’s tool set all the way from the basics of the editor and the visual *ing system blueprint to the in-depth low-level creation of content using C++. This book will provide you with the skills you need to create feature-rich, captivating, and refined game titles with Unreal Engine 4. This book will take you through the creation of four unique game projects, designed so that you will be ready to apply the engine’s rich development capabilities. You will learn not only to take advantage of the visual tools of the engine, but also the vast and powerful programming feature set of Unreal Engine 4. Style and approach The best resource that any beginner level game developer can dream of with examples on leveraging the amazing graphics engine, beautiful character animation and game world generations etc. by means of exciting real world game generation.This book would be a very unique resource for any game developer who wants to get up and running with Unreal. The unique example-driven approach will take you through the most basic games towards the more complex ones and will gradually build your skill level.

Create stunning web applications and Restful APIs from start to finish with Express, Loopback, MongoDB, and MySQL using this definitive guide About This Book Create stunning applications with Node.js from scratch, no matter the goal Discover a wide variety of applications you can effectively integrate third-party libraries and other front-end frameworks with Node.js Leverage all the new features introduced in Node.js 6.X Who This Book Is For This book caters to developers who are looking to build projects right from a simple website to more complex one such as a blog, chat application, a photography site, and a lot more. A Basic knowledge of JavaScript and Node.js would be extremely beneficial. What You Will Learn Explore MVC design pattern in Node.js Build solid architectures by following test-driven development Look beyond web applications and create your own desktop app with Node.js Develop single page applications using Node.js with the RESTful APIs, MongoDB, and ORM Master the Express framework and build a complete application with a real database Create a real-time and fully functional online chat application with Socket.IO In Detail Node.js is the most popular framework to create server-side applications today. Be it web, desktop, or mobile, Node.js comes to your rescue to create stunning real-time applications. Node.js 6.x Blueprints will teach you to build these types of projects in an easy-to-understand manner. The key to any Node.js project is a strong foundation on the concepts that will be a part of every project. The book will first teach you the MVC design pattern while developing a Twitter-like application using Express.js. In the next chapters, you will learn to create a website and applications such as streaming, photography, and a store locator using MongoDB, MySQL, and Firebase. Once you’re warmed up, we’ll move on to more complex projects such as a consumer feedback app, a real-time chat app, and a blog using Node.js with frameworks such as loopback.io and socket.io. Finally, we’ll explore front-end build processes, Docker, and continuous delivery. By the end of book, you will be comfortable working with Node.js applications and will know the best tools and frameworks to build highly scalable desktop and cloud applications. Style and approach This is an easy-to-follow guide full of practical examples. This book takes a project-based approach and each chapter contains step-by-step instructions to create stunning applications across different application domains from scratch.

Exciting projects that will teach you how complex data can be exploited to gain maximum insights About This Book Architect a good HBase cluster for a very large distributed system Get to grips with the concepts of performance tuning with HBase A practical guide full of engaging recipes and attractive screenshots to enhance your system’s performance Who This Book Is For This book is intended for developers and architects who want to know all about HBase at a hands-on level. This book is also for big data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic scalable database solution in the big data space. What You Will Learn Configure HBase from a high performance perspective Grab data from various RDBMS/Flat files into the HBASE systems Understand table design and perform CRUD operations Find out how the communication between the client and server happens in HBase Grasp when to use and avoid MapReduce and how to perform various tasks with it Get to know the concepts of scaling with HBase through practical examples Set up Hbase in the Cloud for a small scale environment Integrate HBase with other tools including ElasticSearch In Detail Apache HBase is a non-relational NoSQL database management system that runs on top of HDFS. It is an open source, disturbed, versioned, column-oriented store and is written in Java to provide random real-time access to big Data. We’ll start off by ensuring you have a solid understanding the basics of HBase, followed by giving you a thorough explanation of architecting a HBase cluster as per our project specifications. Next, we will explore the scalable structure of tables and we will be able to communicate with the HBase client. After this, we’ll show you the intricacies of MapReduce and the art of performance tuning with HBase. Following this, we’ll explain the concepts pertaining to scaling with HBase. Finally, you will get an understanding of how to integrate HBase with other tools such as ElasticSearch. By the end of this book, you will have learned enough to exploit HBase for boost system performance. Style and approach This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications. This books also provides examples for C#, Python, and Ruby users.

Master the intricacies of Tableau to create effective data visualizations About This Book Arm yourself with an arsenal of advanced chart types and geocoding to efficiently and engagingly present information Map a grid over a network node diagram and use that grid to demonstrate loads, processing time, and more in Tableau Integrate R with Tableau by utilizing R functions, libraries, and saved models Who This Book Is For If you are a business analyst without developer-level programming skills, then this book is for you. You are expected to have at least a fundamental understanding of Tableau and basic knowledge of joins, however SQL knowledge is not assumed. You should have basic computer skills, including at least moderate Excel proficiency. What You Will Learn Create a worksheet that can display the current balance for any given period in time Recreate a star schema from in a data warehouse in Tableau Combine level of detail calculations with table calculations, sets, and parameters Create custom polygons to build filled maps for area codes in the USA Visualize data using a set of analytical and advanced charting techniques Know when to use Tableau instead of PowerPoint Build a dashboard and export it to PowerPoint In Detail Tableau has emerged as one of the most popular Business Intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. This book will empower you to become a master in Tableau by exploiting the many new features introduced in Tableau 10.0. You will embark on this exciting journey by getting to know the valuable methods of utilizing advanced calculations to solve complex problems. These techniques include creative use of different types of calculations such as row-level, aggregate-level, and more. You will discover how almost any data visualization challenge can be met in Tableau by getting a proper understanding of the tool’s inner workings and creatively exploring possibilities. You’ll be armed with an arsenal of advanced chart types and techniques to enable you to efficiently and engagingly present information to a variety of audiences through the use of clear, efficient, and engaging dashboards. Explanations and examples of efficient and inefficient visualization techniques, well-designed and poorly designed dashboards, and compromise options when Tableau consumers will not embrace data visualization will build on your understanding of Tableau and how to use it efficiently. By the end of the book, you will be equipped with all the information you need to create effective dashboards and data visualization solutions using Tableau. Style and approach This book takes a direct approach, to systematically evolve to more involved functionalities such as advanced calculation, parameters & sets, data blending and R integration. This book will help you gain skill in building visualizations previously beyond your capacity.

Learn to get the most out of your business data to optimize your business About This Book This book will enable and empower you to break free of the shackles of spreadsheets Learn to make informed decisions using the data at hand with this highly practical, comprehensive guide This book includes real-world use cases that teach you how analytics can be put to work to optimize your business Using a fictional transactional dataset in raw form, you’ll work your way up to ultimately creating a fully-functional warehouse and a fleshed-out BI platform Who This Book Is For This book is for anyone who has wrangled with data to try to perform automated data analysis through visualizations for themselves or their customers. This highly-customized guide is for developers who know a bit about analytics but don't know how to make use of it in the field of business intelligence. What You Will Learn Create a BI environment that enables self-service reporting Understand SQL and the aggregation of data Develop a data model suitable for analytical reporting Connect a data warehouse to the analytic reporting tools Understand the specific benefits behind visualizations with D3.js, R, Tableau, QlikView, and Python Get to know the best practices to develop various reports and applications when using BI tools Explore the field of data analysis with all the data we will use for reporting In Detail Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis. Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business. The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company. It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market. Style and approach Packed with real-world examples, this pragmatic guide helps you polish your data and make informed decisions for your business. We cover both business and data analysis perspectives, blending theory and practical hands-on work so that you perceive data as a business asset.

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*

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

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

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

"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 "

Learn how to create more powerful data mining applications with this comprehensive Python guide to advance data analytics techniques About This Book Dive deeper into data mining with Python – don’t be complacent, sharpen your skills! From the most common elements of data mining to cutting-edge techniques, we’ve got you covered for any data-related challenge Become a more fluent and confident Python data-analyst, in full control of its extensive range of libraries Who This Book Is For This book is for data scientists who are already familiar with some basic data mining techniques such as SQL and machine learning, and who are comfortable with Python. If you are ready to learn some more advanced techniques in data mining in order to become a data mining expert, this is the book for you! What You Will Learn Explore techniques for finding frequent itemsets and association rules in large data sets Learn identification methods for entity matches across many different types of data Identify the basics of network mining and how to apply it to real-world data sets Discover methods for detecting the sentiment of text and for locating named entities in text Observe multiple techniques for automatically extracting summaries and generating topic models for text See how to use data mining to fix data anomalies and how to use machine learning to identify outliers in a data set In Detail Data mining is an integral part of the data science pipeline. It is the foundation of any successful data-driven strategy – without it, you'll never be able to uncover truly transformative insights. Since data is vital to just about every modern organization, it is worth taking the next step to unlock even greater value and more meaningful understanding. If you already know the fundamentals of data mining with Python, you are now ready to experiment with more interesting, advanced data analytics techniques using Python's easy-to-use interface and extensive range of libraries. In this book, you'll go deeper into many often overlooked areas of data mining, including association rule mining, entity matching, network mining, sentiment analysis, named entity recognition, text summarization, topic modeling, and anomaly detection. For each data mining technique, we'll review the state-of-the-art and current best practices before comparing a wide variety of strategies for solving each problem. We will then implement example solutions using real-world data from the domain of software engineering, and we will spend time learning how to understand and interpret the results we get. By the end of this book, you will have solid experience implementing some of the most interesting and relevant data mining techniques available today, and you will have achieved a greater fluency in the important field of Python data analytics. Style and approach This book will teach you the intricacies in applying data mining using real-world scenarios and will act as a very practical solution to your data mining needs.