Master over 60 recipes to help you deliver complete, scalable, microservice-based solutions and see the improved business results immediately About This Book Adopt microservices-based architecture and deploy it at scale Build your complete microservice architecture using different recipes for different solutions Identify specific tools for specific scenarios and deliver immediate business results, correlate use cases, and adopt them in your team and organization Who This Book Is For This book is for developers, ops, and DevOps professionals who would like to put microservices to work and improve products, services, and operations. Those looking to build and deploy microservices will find this book useful, as well as managers and people at CXO level looking to adopt microservices in their organization. Prior knowledge of Java is expected. No prior knowledge of microservices is assumed. What You Will Learn Build microservices using Spring Boot, Wildfly Swarm, Dropwizard, and SparkJava Containerize your microservice using Docker Deploy microservices using Mesos/Marathon and Kubernetes Implement service discovery and load balancing using Zookeeper, Consul, and Nginx Monitor microservices using Graphite and Grafana Write stream programs with Kafka Streams and Spark Aggregate and manage logs using Kafka Get introduced to DC/OS, Docker Swarm, and YARN In Detail This book will help any team or organization understand, deploy, and manage microservices at scale. It is driven by a sample application, helping you gradually build a complete microservice-based ecosystem. Rather than just focusing on writing a microservice, this book addresses various other microservice-related solutions: deployments, clustering, load balancing, logging, streaming, and monitoring. The initial chapters offer insights into how web and enterprise apps can be migrated to scalable microservices. Moving on, you’ll see how to Dockerize your application so that it is ready to be shipped and deployed. We will look at how to deploy microservices on Mesos and Marathon and will also deploy microservices on Kubernetes. Next, you will implement service discovery and load balancing for your microservices. We’ll also show you how to build asynchronous streaming systems using Kafka Streams and Apache Spark. Finally, we wind up by aggregating your logs in Kafka, creating your own metrics, and monitoring the metrics for the microservice. Style and approach This book follows a recipe-driven approach and shows you how to plug and play with all the various pieces, putting them together to build a complete scalable microservice ecosystem. You do not need to study the chapters in order, as you can directly refer to the content you need for your situation.

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.

Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you’ll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that’s based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.

Get acquainted with the world of LXC About This Book Get the most practical and up-to-date resource on LXC and take full advantage of what Linux containers can offer in the day-to-day operations of large-scale applications Learn how to deploy and administer various workloads such as web applications inside LXC Save your organization time and money by building robust and secure containers and by speeding the deployment process of your software Who This Book Is For This book is for Linux engineers and software developers who are looking to deploy applications in a fast, secure, and scalable way for use in testing and production. What You Will Learn Deep dive into the foundations of Linux containers with kernel namespaces and cgroups Install, configure, and administer Linux containers with LXC and libvirt Begin writing applications using Python libvirt bindings Take an in-depth look at container networking Set up monitoring and security with LXC Build and deploy a highly available application with LXC in the cloud In Detail In recent years, containers have gained wide adoption by businesses running a variety of application loads. This became possible largely due to the advent of kernel namespaces and better resource management with control groups (cgroups). Linux containers (LXC) are a direct implementation of those kernel features that provide operating system level virtualization without the overhead of a hypervisor layer. This book starts by introducing the foundational concepts behind the implementation of LXC, then moves into the practical aspects of installing and configuring LXC containers. Moving on, you will explore container networking, security, and backups. You will also learn how to deploy LXC with technologies like Open Stack and Vagrant. By the end of the book, you will have a solid grasp of how LXC is implemented and how to run production applications in a highly available and scalable way. Style and approach A practical guide that introduces the core technologies behind Linux containers and provides a deep dive into installation, configuration, and operations of LXC.

Over 90 practical, actionable recipes to automate, test, and manage your infrastructure quickly and effectively About This Book Bring down your delivery timeline from days to hours by treating your server configurations and VMs as code, just like you would with software code. Take your existing knowledge and skill set with your existing tools (Puppet, Chef, or Docker) to the next level and solve IT infrastructure challenges. Use practical recipes to use code to provision and deploy servers and applications and have greater control of your infrastructure. Who This Book Is For This book is for DevOps engineers and developers working in cross-functional teams or operations and would now switch to IAC to manage complex infrastructures. What You Will Learn Provision local and remote development environments with Vagrant Automate production infrastructures with Terraform, Ansible and Cloud-init on AWS, OpenStack, Google Cloud, Digital Ocean, and more Manage and test automated systems using Chef and Puppet Build, ship, and debug optimized Docker containers Explore the best practices to automate and test everything from cloud infrastructures to operating system configuration In Detail Infrastructure as Code (IAC) is a key aspect of the DevOps movement, and this book will show you how to transform the way you work with your infrastructure—by treating it as software. This book is dedicated to helping you discover the essentials of infrastructure automation and its related practices; the over 90 organized practical solutions will demonstrate how to work with some of the very best tools and cloud solutions. You will learn how to deploy repeatable infrastructures and services on AWS, OpenStack, Google Cloud, and Digital Ocean. You will see both Ansible and Terraform in action, manipulate the best bits from cloud-init to easily bootstrap instances, and simulate consistent environments locally or remotely using Vagrant. You will discover how to automate and test a range of system tasks using Chef or Puppet. You will also build, test, and debug various Docker containers having developers’ interests in mind. This book will help you to use the right tools, techniques, and approaches to deliver working solutions for today’s modern infrastructure challenges. Style and approach This is a recipe-based book that allows you to venture into some of the most cutting-edge practices and techniques about IAC and solve immediate problems when trying to implement them.

Master the intricacies of Elasticsearch 5 and use it to create flexible and scalable search solutions About This Book Master the searching, indexing, and aggregation features in ElasticSearch Improve users’ search experience with Elasticsearch’s functionalities and develop your own Elasticsearch plugins A comprehensive, step-by-step guide to master the intricacies of ElasticSearch with ease Who This Book Is For If you have some prior working experience with Elasticsearch and want to take your knowledge to the next level, this book will be the perfect resource for you.If you are a developer who wants to implement scalable search solutions with Elasticsearch, this book will also help you. Some basic knowledge of the query DSL and data indexing is required to make the best use of this book. What You Will Learn Understand Apache Lucene and Elasticsearch 5’s design and architecture Use and configure the new and improved default text scoring mechanism in Apache Lucene 6 Know how to overcome the pitfalls while handling relational data in Elasticsearch Learn about choosing the right queries according to the use cases and master the *ing module including new default *ing language, painlessly Explore the right way of scaling production clusters to improve the performance of Elasticsearch Master the searching, indexing, and aggregation features in Elasticsearch Develop your own Elasticsearch plugins to extend the functionalities of Elasticsearch In Detail Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. This book will give you a brief recap of the basics and also introduce you to the new features of Elasticsearch 5. We will guide you through the intermediate and advanced functionalities of Elasticsearch, such as querying, indexing, searching, and modifying data. We’ll also explore advanced concepts, including aggregation, index control, sharding, replication, and clustering. We’ll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your Elasticsearch cluster to contextualize it and improve its performance. We’ll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use. Style and approach This comprehensive guide covers intermediate and advanced concepts in Elasticsearch as well as their implementation. An easy-to-follow approach means you’ll be able to master even advanced querying, searching, and administration tasks with ease.

Learn idiomatic, efficient, clean, and extensible Go design and concurrency patterns by using TDD About This Book A highly practical guide filled with numerous examples unleashing the power of design patterns with Go. Discover an introduction of the CSP concurrency model by explaining GoRoutines and channels. Get a full explanation, including comprehensive text and examples, of all known GoF design patterns in Go. Who This Book Is For The target audience is both beginner- and advanced-level developers in the Go programming language. No knowledge of design patterns is expected. What You Will Learn All basic syntax and tools needed to start coding in Go Encapsulate the creation of complex objects in an idiomatic way in Go Create unique instances that cannot be duplicated within a program Understand the importance of object encapsulation to provide clarity and maintainability Prepare cost-effective actions so that different parts of the program aren’t affected by expensive tasks Deal with channels and GoRoutines within the Go context to build concurrent application in Go in an idiomatic way In Detail Go is a multi-paradigm programming language that has built-in facilities to create concurrent applications. Design patterns allow developers to efficiently address common problems faced during developing applications. Go Design Patterns will provide readers with a reference point to software design patterns and CSP concurrency design patterns to help them build applications in a more idiomatic, robust, and convenient way in Go. The book starts with a brief introduction to Go programming essentials and quickly moves on to explain the idea behind the creation of design patterns and how they appeared in the 90’s as a common "language" between developers to solve common tasks in object-oriented programming languages. You will then learn how to apply the 23 Gang of Four (GoF) design patterns in Go and also learn about CSP concurrency patterns, the "killer feature" in Go that has helped Google develop software to maintain thousands of servers. With all of this the book will enable you to understand and apply design patterns in an idiomatic way that will produce concise, readable, and maintainable software. Style and approach This book will teach widely used design patterns and best practices with Go in a step-by-step manner. The code will have detailed examples, to allow programmers to apply design patterns in their day-to-day coding.

Over 70 recipes to get you writing powerful and efficient multithreaded, asynchronous, and parallel programs in C# 6.0 About This Book Rewritten and updated to take advantage of the latest C# 6 features Learn about multithreaded, asynchronous, and parallel programming through hands-on, code-first examples Use these recipes to build fast, scalable, and reliable applications in C# Who This Book Is For This book is aimed at those who are new to multithreaded programming, and who are looking for a quick and easy way to get started. It is assumed that you have some experience in C# and .NET already, and you should also be familiar with basic computer science terminology and basic algorithms and data structures. What You Will Learn Use C# 6.0 asynchronous language features Work with raw threads, synchronize threads, and coordinate their work Develop your own asynchronous API with Task Parallel Library Work effectively with a thread pool Scale up your server application with I/O threads Parallelize your LINQ queries with PLINQ Use common concurrent collections Apply different parallel programming patterns Use Reactive Extensions to run asynchronous operations and manage their options In Detail Multi-core processors are synonymous with computing speed and power in today’s world, which is why multithreading has become a key concern for C# developers. Multithreaded code helps you create effective, scalable, and responsive applications. This is an easy-to-follow guide that will show you difficult programming problems in context. You will learn how to solve them with practical, hands-on, recipes. With these recipes, you’ll be able to start creating your own scalable and reliable multithreaded applications. Starting from learning what a thread is, we guide you through the basics and then move on to more advanced concepts such as task parallel libraries, C# asynchronous functions, and much more. Rewritten to the latest C# specification, C# 6, and updated with new and modern recipes to help you make the most of the hardware you have available, this book will help you push the boundaries of what you thought possible in C#. Style and approach This is an easy-to-follow guide full of hands-on examples of real-world multithreading tasks. Each topic is explained and placed in context, and for the more inquisitive, there are also more in-depth details of the concepts used.

Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Build effective applications by applying Odoo development best practices About This Book Each recipe stands by itself as much as possible, so that you can jump straight into the topics you prefer The recipes included cover all the major development areas of Odoo and the most important techniques explained through real-life projects From seasoned authors, learn the tricks of becoming a productive developer with the Odoo framework Who This Book Is For If you are a Python developer who wants to learn or consolidate your Odoo development skills, then this book is for you! Some experience with the JavaScript programming language and web development is required to fully benefit from the front-end chapters. What You Will Learn Install and manage Odoo environments and instances Use Models to define your application's data structures Add business logic to your applications Implement automated tests and debug Odoo apps Use back-end views to create a user interface Get to know about the access security model and internationalization features Develop front-end website features Extend the web client with new widgets and features In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source is also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. The book starts by covering Odoo installation and administration, and provides a gentle introduction to application development. It then dives deep into several of the areas that an experienced developer will need to use. You’ll learn implement business logic, adapt the UI, and extend existing features. Style and Approach These practical and easy-to-follow recipes are presented step-by-step, with dozens of hands-on recipes to boost your Odoo skills. This book can also be used as a reference guide for your daily work.

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.

This book is a step-by-step tutorial that includes complete source code for all of the games covered. It adopts an engaging style to teach all the game development concepts. Each block of code is explained, and game development concepts are diagrammed and covered in detail. Each game begins with a concept de*ion and concludes with suggestions for expanding on the finished game. This book is intended for readers who want to create 3D games using the XNA Framework. Basic knowledge of the C# programming language and 2D XNA concepts are helpful, but not required.

This is a step-by-step tutorial enriched with practical examples and the necessary screenshots for easy and quick learning. This book is for you if you are a Java developer or a Team Manager familiar with Java and want to ensure the quality of your code using Sonar. You should have a background with Java and unit testing in general.

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

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

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

Aimed at those who want to overcome the limitations of CSS, through this book you will begin to harness the efficiency of Less by building advanced, responsive, and modern websites. Experienced web developers, students, and even web designers will find this guide very useful as they enhance their CSS skills.

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.

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