Build and customize a wide range of powerful Unity AI systems with over 70 hands-on recipes and techniques About This Book Empower your agent with decision making capabilities using advanced minimaxing and Negamaxing techniques Discover how AI can be applied to a wide range of games to make them more interactive. Instigate vision and hearing abilities in your agent through collider based and graph based systems Who This Book Is For This book is intended for those who already have a basic knowledge of Unity and are eager to get more tools under their belt to solve AI and gameplay-related problems. What You Will Learn Use techniques such as A*and A*mbush to empower your agents with path finding capabilities. Create a representation of the world and make agents navigate it Construct decision-making systems to make the agents take different actions Make different agents coordinate actions and create the illusion of technical behavior Simulate senses and apply them in an awareness system Design and implement AI in board games such as Tic-Tac-Toe and Checkers Implement efficient prediction mechanism in your agents with algorithms such as N-Gram predictor and na?ve Bayes classifier Understand and analyze how the influence maps work. In Detail Unity 5 comes fully packaged with a toolbox of powerful features to help game and app developers create and implement powerful game AI. Leveraging these tools via Unity’s API or built-in features allows limitless possibilities when it comes to creating your game’s worlds and characters. This practical Cookbook covers both essential and niche techniques to help you be able to do that and more. This Cookbook is engineered as your one-stop reference to take your game AI programming to the next level. Get to grips with the essential building blocks of working with an agent, programming movement and navigation in a game environment, and improving your agent's decision making and coordination mechanisms - all through hands-on examples using easily customizable techniques. Discover how to emulate vision and hearing capabilities for your agent, for natural and humanlike AI behaviour, and improve them with the help of graphs. Empower your AI with decision-making functions through programming simple board games such as Tic-Tac-Toe and Checkers, and orchestrate agent coordination to get your AIs working together as one. Style and approach This recipe-based guide will take you through implementing various AI algorithms. Each topic is explained and placed among other related techniques, sometimes building on the knowledge from previous chapters. There are also references to more technical books and papers, so you can dig deeper if you want to.

Master the art of machine learning with .NET and gain insight into real-world applications About This Book Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0 Set up your business application to start using machine learning techniques Familiarize the user with some of the more common .NET libraries for machine learning Implement several common machine learning techniques Evaluate, optimize and adjust machine learning models Who This Book Is For This book is targeted at .Net developers who want to build complex machine learning systems. Some basic understanding of data science is required. What You Will Learn Write your own machine learning applications and experiments using the latest .NET framework, including .NET Core 1.0 Set up your business application to start using machine learning. Accurately predict the future using regressions. Discover hidden patterns using decision trees. Acquire, prepare, and combine datasets to drive insights. Optimize business throughput using Bayes Classifier. Discover (more) hidden patterns using KNN and Na?ve Bayes. Discover (even more) hidden patterns using K-Means and PCA. Use Neural Networks to improve business decision making while using the latest ASP.NET technologies. Explore “Big Data”, distributed computing, and how to deploy machine learning models to IoT devices – making machines self-learning and adapting Along the way, learn about Open Data, Bing maps, and MBrace In Detail .Net is one of the widely used platforms for developing applications. With the meteoric rise of Machine learning, developers are now keen on finding out how can they make their .Net applications smarter. Also, .NET developers are interested into moving into the world of devices and how to apply machine learning techniques to, well, machines. This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin with introduction to F# and prepare yourselves for machine learning using .NET framework. You will be writing a simple linear regression model using an example which predicts sales of a product. Forming a base with the regression model, you will start using machine learning libraries available in .NET framework such as Math.NET, Numl.NET and Accord.NET with the help of a sample application. You will then move on to writing multiple linear regressions and logistic regressions. You will learn what is open data and the awesomeness of type providers. Next, you are going to address some of the issues that we have been glossing over so far and take a deep dive into obtaining, cleaning, and organizing our data. You will compare the utility of building a KNN and Naive Bayes model to achieve best possible results. Implementation of Kmeans and PCA using Accord.NET and Numl.NET libraries is covered with the help of an example application. We will then look at many of issues confronting creating real-world machine learning models like overfitting and how to combat them using confusion matrixes, scaling, normalization, and feature selection. You will now enter into the world of Neural Networks and move your line of business application to a hybrid scientific application. After you have covered all the above machine learning models, you will see how to deal with very large datasets using MBrace and how to deploy machine learning models to Internet of Thing (IoT) devices so that the machine can learn and adapt on the fly. Style and approach This book will guide you in learning everything about how to tackle the flood of data being encountered these days in your .NET applications with the help of popular machine learning libraries offered by the .NET framework.

Secure your Linux machines and keep them secured with the help of exciting recipes About This Book This book provides code-intensive discussions with detailed recipes that help you understand better and learn faster. More than 50 hands-on recipes to create and administer a secure Linux system locally as well as on a network Enhance file system security and local and remote user authentication by using various security tools and different versions of Linux for different tasks Who This Book Is For Practical Linux Security Cookbook is intended for all those Linux users who already have knowledge of Linux File systems and administration. You should be familiar with basic Linux commands. Understanding Information security and its risks to a Linux system is also helpful in understanding the recipes more easily. However, even if you are unfamiliar with Information security, you will be able to easily follow and understand the recipes discussed. Since Linux Security Cookbook follows a practical approach, following the steps is very easy. What You Will Learn Learn about various vulnerabilities and exploits in relation to Linux systems Configure and build a secure kernel and test it Learn about file permissions and security and how to securely modify files Explore various ways to authenticate local users while monitoring their activities. Authenticate users remotely and securely copy files on remote systems Review various network security methods including firewalls using iptables and TCP Wrapper Explore various security tools including Port Sentry, Squid Proxy, Shorewall, and many more Understand Bash vulnerability/security and patch management In Detail With the growing popularity of Linux, more and more administrators have started moving to the system to create networks or servers for any task. This also makes Linux the first choice for any attacker now. Due to the lack of information about security-related attacks, administrators now face issues in dealing with these attackers as quickly as possible. Learning about the different types of Linux security will help create a more secure Linux system. Whether you are new to Linux administration or experienced, this book will provide you with the skills to make systems more secure. With lots of step-by-step recipes, the book starts by introducing you to various threats to Linux systems. You then get to walk through customizing the Linux kernel and securing local files. Next you will move on to manage user authentication locally and remotely and also mitigate network attacks. Finally, you will learn to patch bash vulnerability and monitor system logs for security. With several screenshots in each example, the book will supply a great learning experience and help you create more secure Linux systems. Style and approach An easy-to-follow cookbook with step-by-step practical recipes covering the various Linux security administration tasks. Each recipe has screenshots, wherever needed, to make understanding more easy.

This hands-on guide is aimed at practitioners of data science. The book assumes some previous skills with Julia and skills in coding in a *ing language such as Python or R, or a compiled language such as C or Java.

This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.

This book is intended for mobile security professionals who want to learn how to secure iOS operating systems and its applications. Any knowledge of iOS architecture would be an added advantage.

This book is intended for the budding data scientist, predictive modeler, or quantitative analyst with only a basic exposure to R and statistics. It is also designed to be a reference for experienced professionals wanting to brush up on the details of a particular type of predictive model. Mastering Predictive Analytics with R assumes familiarity with only the fundamentals of R, such as the main data types, simple functions, and how to move data around. No prior experience with machine learning or predictive modeling is assumed, however you should have a basic understanding of statistics and calculus at a high school level.

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

If you are an experienced Android developer wanting to enhance your skills with the Gradle Android build system, then this book is for you. As a prerequisite, you will need some knowledge of the concepts of Android application development.

Master the fundamentals of malware analysis for the Windows platform and enhance your anti-malware skill set About This Book Set the baseline towards performing malware analysis on the Windows platform and how to use the tools required to deal with malware Understand how to decipher x86 assembly code from source code inside your favourite development environment A step-by-step based guide that reveals malware analysis from an industry insider and demystifies the process Who This Book Is For This book is best for someone who has prior experience with reverse engineering Windows executables and wants to specialize in malware analysis. The book presents the malware analysis thought process using a show-and-tell approach, and the examples included will give any analyst confidence in how to approach this task on their own the next time around. What You Will Learn Use the positional number system for clear conception of Boolean algebra, that applies to malware research purposes Get introduced to static and dynamic analysis methodologies and build your own malware lab Analyse destructive malware samples from the real world (ITW) from fingerprinting and static/dynamic analysis to the final debrief Understand different modes of linking and how to compile your own libraries from assembly code and integrate the codein your final program Get to know about the various emulators, debuggers and their features, and sandboxes and set them up effectively depending on the required scenario Deal with other malware vectors such as pdf and MS-Office based malware as well as *s and shellcode In Detail Windows OS is the most used operating system in the world and hence is targeted by malware writers. There are strong ramifications if things go awry. Things will go wrong if they can, and hence we see a salvo of attacks that have continued to disrupt the normal scheme of things in our day to day lives. This book will guide you on how to use essential tools such as debuggers, disassemblers, and sandboxes to dissect malware samples. It will expose your innards and then build a report of their indicators of compromise along with detection rule sets that will enable you to help contain the outbreak when faced with such a situation. We will start with the basics of computing fundamentals such as number systems and Boolean algebra. Further, you'll learn about x86 assembly programming and its integration with high level languages such as C++.You'll understand how to decipher disassembly code obtained from the compiled source code and map it back to its original design goals. By delving into end to end analysis with real-world malware samples to solidify your understanding, you'll sharpen your technique of handling destructive malware binaries and vector mechanisms. You will also be encouraged to consider analysis lab safety measures so that there is no infection in the process. Finally, we'll have a rounded tour of various emulations, sandboxing, and debugging options so that you know what is at your disposal when you need a specific kind of weapon in order to nullify the malware. Style and approach An easy to follow, hands-on guide with de*ions and screenshots that will help you execute effective malicious software investigations and conjure up solutions creatively and confidently.

This book is a handson, practical guide that will help readers to understand the various capabilities of VMware Fusion with the help of realworld examples. This book is a must for every Mac user out there who is in the process of transitioning from Windows to OS X. Whether you’re new to Fusion or you’ve been using it for years, there’s something new for everyone to learn.

Taking a recipebased approach, this book presents numerous practical examples that you can use directly in your applications. The book covers the essential issues you will face while developing your web applications and gives you solutions to them. The recipes in this book are written in a manner that rapidly takes you from beginner to expert level. This book is for web developers of all skill levels. Although some knowledge of JavaScript, HTML, and CSS is required, this Cookbook will teach jQuery newcomers all the basics required to move on to the more complex examples of this book, which will benefit the more seasoned jQuery developer. If you want to learn how to create modern website features quickly, using best practice techniques, then this book is for you.

This book is written by a gamer, for a gamer to guide just about anything with Source SDK giving a firm grasp of all the tools it has to offer using stepbystep explanations. If you’re a keen gamer who wants a bit more out of your favorite game and create your own modifications (mods) and levels with the Source engine, this book is great for you. No programming and Source SDK experience is required.

Use PhoneGap to build cross-platform mobile applications quickly and efficiently About This Book Build native mobile phone applications with HTML5, JavaScript, and CSS Incorporate smartphone capabilities such as GPS, camera, accelerometer, and more into your apps for any mobile platform Use Cordova view to embed PhoneGap into native applications to either transit smoothly to PhoneGap or incorporate PhoneGap functionalities Who This Book Is For If you are a mobile application developer in iOS or Android, or a web application developer who wants to learn how to make cross-platform mobile applications using PhoneGap, this book is perfect for you. To make the most of this book, it will be helpful if you have prior knowledge of HTML5, CSS, and JavaScript. What You Will Learn Get to grips with the fundamentals of PhoneGap to get started Set up a development environment for Linux, Mac OS, and Windows Use Cordova CLI, workflows, and Plugman Plugin manager to create mobile applications efficiently Understand the development workflow to create native cross-platform mobile applications Embed plugin support to transition to PhoneGap or use it to enhance existing applications Improve your mobile development knowledge using object-oriented programming (OOP), reusable components, and AJAX closures Be empowered to build your own mobile apps quickly with ease Discover tips and tricks to make app development fun and easy In Detail PhoneGap is an open source framework that allows you to quickly build cross-platform mobile apps using HTML5, JavaScript, and CSS. PhoneGap Build is a cloud service that allows you to quickly develop and compile mobile applications without SDKs, compilers, and hardware. PhoneGap allows you to use its existing plugins or create new ones, as per your requirements, to enhance your mobile applications. Starting by installing PhoneGap, you’ll develop an app that uses various device capabilities through different plugins and learn how to build an app in the cloud with PhoneGap’s Build service. You’ll discover how to use PhoneGap to create an application view, along with how to use a camera, geolocation, and other device capabilities to create engaging apps. Next, you’ll augment applications with PhoneGap's plugins using minimalistic code. You’ll explore the app preparation process to deploy your app to the app store. By the end of the book, you’ll have also learned how to apply hybrid mobile UIs that will work across different platforms and different screen sizes for better user experience. Style and approach This is an example-based, fast-paced guide that covers the fundamentals of creating cross-platform mobile applications with PhoneGap.

This book is a practical, stepbystep tutorial providing a complete reference guide to the setup, installation, and administration of ArcGIS Server technology. If you are a GIS user, analyst, DBA, or programmer with a basic knowledge of ESRI GIS, then this book is for you.

An easytofollow, stepbystep tutorial focusing on practical situations and manipulations, guiding you to create a concrete Graphical User Interface and a simple 2D game. If you are a Unity 3D developer looking forward to learn NGUI for Unity, then this book is for you. Prior knowlege of C# *ing is expected. Additional knowledge of Unity 3D Editor, GameObject and creating/adding *s to GameObject would be beneficial; however, no prior knowledge of NGUI is required.

Build, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of real-world applications with complete Scala code. A concise guide to processing large-scale networks with Apache Spark. Who This Book Is For This book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. Basic programming experience with Scala is assumed. Basic knowledge of Spark is assumed. What You Will Learn Write, build and deploy Spark applications with the Scala Build Tool. Build and analyze large-scale network datasets Analyze and transform graphs using RDD and graph-specific operations Implement new custom graph operations tailored to specific needs. Develop iterative and efficient graph algorithms using message aggregation and Pregel abstraction Extract subgraphs and use it to discover common clusters Analyze graph data and solve various data science problems using real-world datasets. In Detail Apache Spark is the next standard of open-source cluster-computing engine for processing big data. Many practical computing problems concern large graphs, like the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. Apache Spark GraphX API combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. This book will teach the user to do graphical programming in Apache Spark, apart from an explanation of the entire process of graphical data analysis. You will journey through the creation of graphs, its uses, its exploration and analysis and finally will also cover the conversion of graph elements into graph structures. This book begins with an introduction of the Spark system, its libraries and the Scala Build Tool. Using a hands-on approach, this book will quickly teach you how to install and leverage Spark interactively on the command line and in a standalone Scala program. Then, it presents all the methods for building Spark graphs using illustrative network datasets. Next, it will walk you through the process of exploring, visualizing and analyzing different network characteristics. This book will also teach you how to transform raw datasets into a usable form. In addition, you will learn powerful operations that can be used to transform graph elements and graph structures. Furthermore, this book also teaches how to create custom graph operations that are tailored for specific needs with efficiency in mind. The later chapters of this book cover more advanced topics such as clustering graphs, implementing graph-parallel iterative algorithms and learning methods from graph data. Style and approach A step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical examples that will ensure an overall understanding of the concepts of Spark.

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world’s leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you’ll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Over 100 recipes to help you develop cross-platform, native applications in JavaScript About This Book Leverage your JavaScript skills to write mobile applications using Titanium Studio tools with the native advantage Deploy your application on the App Store and Google Play Add your own IOS native modules in objective-C, in an easy-to-follow step-by-step format Who This Book Is For This book is an essential for any developer learning or using JavaScript who wants to write native UI applications for iOS and Android. No knowledge of Objective-C, Swift and Java is required and you’ll quickly be developing native, cross-platform apps, in JavaScript! What You Will Learn Transfer data between applications with URL schemes, and make your application accessible to other mobile applications and services Connect with remote services using JSON Work with Google Maps and Apple Maps, GPS and annotate routes Create animations and special effects Integrate notifications and connect with social media services such as Facebook and Twitter Build applications with Alloy MVC – a rapid application development framework Design native APIs and use local databases In Detail The mobile web has paved the way but many users want to have “native” applications installed. Using Appcelerator as a platform it’s now possible to write iOS, Android, and Windows phone applications in JavaScript! It allows developers to develop fully native UI applications using Appcelerator studio tools without any knowledge of Objective-C, Swift or Java. This book will take you through the process of building cross-platform, native UI applications for the mobile from scratch. You will learn how to develop apps, how to use GPS, cameras and photos and how to build socially connected apps. You will also learn how to package them for submission to the App Store and Google Play. This cookbook takes a pragmatic approach to creating applications in JavaScript from putting together basic UIs, to handling events and implementation of third party services such as Twitter, Facebook and Push notifications. The book shows you how to integrate datasources and server APIs, and how to use local databases. The topics covered will guide you to use Appcelerator Studio tools for all the mobile features such as Geolocation, Accelerometer, animation and more. You’ll also learn about Alloy, the Appcelerator MVC framework for rapid app development, and how to transfer data between applications using URLSchemes, enabling other developers to access and launch specific parts of your app. Finally, you will learn how to register developer accounts and publish your very own applications on the App Store and Google Play. Style and approach This book offers a set of practical recipes with a step-by-step approach for building native applications for both the iOS and Android using JavaScript. This hands-on guide shows you exactly how to use the Appcelerator platform to rapidly develop cross-platform, native apps.

Control your machine learning algorithms using test-driven development to achieve quantifiable milestones About This Book Build smart extensions to pre-existing features at work that can help maximize their value Quantify your models to drive real improvement Take your knowledge of basic concepts, such as linear regression and Na?ve Bayes classification, to the next level and productionalize their models Play what-if games with your models and techniques by following the test-driven exploration process Who This Book Is For This book is intended for data technologists (scientists, analysts, or developers) with previous machine learning experience who are also comfortable reading code in Python. You may be starting, or have already started, a machine learning project at work and are looking for a way to deliver results quickly to enable rapid iteration and improvement. Those looking for examples of how to isolate issues in models and improve them will find ideas in this book to move forward. What You Will Learn Get started with an introduction to test-driven development and familiarize yourself with how to apply these concepts to machine learning Build and test a neural network deterministically, and learn to look for niche cases that cause odd model behaviour Learn to use the multi-armed bandit algorithm to make optimal choices in the face of an enormous amount of uncertainty Generate complex and simple random data to create a wide variety of test cases that can be codified into tests Develop models iteratively, even when using a third-party library Quantify model quality to enable collaboration and rapid iteration Adopt simpler approaches to common machine learning algorithms Take behaviour-driven development principles to articulate test intent In Detail Machine learning is the process of teaching machines to remember data patterns, using them to predict future outcomes, and offering choices that would appeal to individuals based on their past preferences. Machine learning is applicable to a lot of what you do every day. As a result, you can’t take forever to deliver your first iteration of software. Learning to build machine learning algorithms within a controlled test framework will speed up your time to deliver, quantify quality expectations with your clients, and enable rapid iteration and collaboration. This book will show you how to quantifiably test machine learning algorithms. The very different, foundational approach of this book starts every example algorithm with the simplest thing that could possibly work. With this approach, seasoned veterans will find simpler approaches to beginning a machine learning algorithm. You will learn how to iterate on these algorithms to enable rapid delivery and improve performance expectations. The book begins with an introduction to test driving machine learning and quantifying model quality. From there, you will test a neural network, predict values with regression, and build upon regression techniques with logistic regression. You will discover how to test different approaches to na?ve bayes and compare them quantitatively, along with how to apply OOP (Object-Oriented Programming) and OOP patterns to test-driven code, leveraging SciKit-Learn. Finally, you will walk through the development of an algorithm which maximizes the expected value of profit for a marketing campaign by combining one of the classifiers covered with the multiple regression example in the book. Style and approach An example-driven guide that builds a deeper knowledge and understanding of iterative machine learning development, test by test. Each topic develops solutions using failing tests to illustrate problems; these are followed by steps to pass the tests, simply and straightforwardly. Topics which use generated data explore how the data was generated, alongside explanations of the assumptions behind different machine learning techniques.

A guide to everything an Oracle SOA Suite 12c administrator needs to hit the ground running About This Book Understand core administrative tasks such as deployments, purging, startup and shutdown, configuration, and backup and recovery Manage, monitor, and troubleshoot SOA composites and OSB services Follow step-by-step instructions to easily and quickly install a highly available two-node cluster Who This Book Is For With topic areas ranging from the simple to the complex, this book is intended for novice, mid-level, and experienced administrators of the Oracle SOA Suite 12c platform as well as Oracle WebLogic Server and Oracle Database administrators interested in diving into the product. What You Will Learn Navigate Oracle Enterprise Manager Fusion Middleware Control Monitor and manage the Oracle SOA Suite 12 c infrastructure Deploy and promote code Monitor and manage services Configure and administer the environment Manage the dehydration store and enterprise scheduler service Troubleshoot Oracle SOA Suite 12c infrastructure Set up backups, recovery, and high availability In Detail Oracle SOA Suite 12 c is the most comprehensive and integrated infrastructure on the market today that is used for building applications based on service-oriented architecture. With the vast number of features and capabilities that Oracle SOA Suite 12c has to offer comes numerous complexities and challenges for administration. Oracle SOA Suite 12c Administrator's Guide covers all the core areas of administration needed for you to effectively manage and monitor the Oracle SOA Suite environment and its transactions, from deployments, to monitoring, to performance tuning, and much, much more. Manage, monitor, and troubleshoot SOA composites and OSB services from a single product set. Understand core administrative activities such as deployments, purging, startup and shutdown, configuration, backup, and recovery. Also learn about new features such as Oracle Enterprise Scheduler, lazy loading, work manager groups, high availability, and more. Style and approach Presented in a reference guide format where chapters can be read in any sequence, this book explains the core concepts while providing real-world implementation specifics, detailing the what, why, and how of all the administration-related activities that involve Oracle SOA Suite 12c. We take a step-by-step approach and offers tips, instructions, and examples that you can easily follow and execute.