Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout About This Book Implement outstanding Machine Learning use cases on your own analytics models and processes. Solutions to common problems when working with the Hadoop ecosystem. Step-by-step implementation of end-to-end big data use cases. Who This Book Is For Readers who have a basic knowledge of big data systems and want to advance their knowledge with hands-on recipes. What You Will Learn Installing and maintaining Hadoop 2.X cluster and its ecosystem. Write advanced Map Reduce programs and understand design patterns. Advanced Data Analysis using the Hive, Pig, and Map Reduce programs. Import and export data from various sources using Sqoop and Flume. Data storage in various file formats such as Text, Sequential, Parquet, ORC, and RC Files. Machine learning principles with libraries such as Mahout Batch and Stream data processing using Apache Spark In Detail Big data is the current requirement. Most organizations produce huge amount of data every day. With the arrival of Hadoop-like tools, it has become easier for everyone to solve big data problems with great efficiency and at minimal cost. Grasping Machine Learning techniques will help you greatly in building predictive models and using this data to make the right decisions for your organization. Hadoop Real World Solutions Cookbook gives readers insights into learning and mastering big data via recipes. The book not only clarifies most big data tools in the market but also provides best practices for using them. The book provides recipes that are based on the latest versions of Apache Hadoop 2.X, YARN, Hive, Pig, Sqoop, Flume, Apache Spark, Mahout and many more such ecosystem tools. This real-world-solution cookbook is packed with handy recipes you can apply to your own everyday issues. Each chapter provides in-depth recipes that can be referenced easily. This book provides detailed practices on the latest technologies such as YARN and Apache Spark. Readers will be able to consider themselves as big data experts on completion of this book. This guide is an invaluable tutorial if you are planning to implement a big data warehouse for your business. Style and approach An easy-to-follow guide that walks you through world of big data. Each tool in the Hadoop ecosystem is explained in detail and the recipes are placed in such a manner that readers can implement them sequentially. Plenty of reference links are provided for advanced reading.

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.

Targeted at those with an existing familiarity with R programming, this practical guide will appeal directly to programmers interested in learning effective data visualization techniques with R and a wide-range of its associated libraries.

This book is aimed at both new developers as well as experienced developers. If you are a new SAP BusinessObjects Universe developer who is looking for a step-by-step guide supported with real-life examples and illustrated diagrams, then this book is for you. If you are a seasoned BusinessObjects Universe developer who is looking for a fast way to map your old experience in Universe designer to the newer Information Design Tool, then this book is for you as well.

If you are a Visual Studio 2013 or .NET developer who would like to sharpen your existing skill set and adapt to new .NET technologies, this is the book for you. A basic understanding of .NET and C# is required.

If you are a business analyst, BI developer, or an IT professional who wants to learn the A to Z of how to work with Web Intelligence reporting tools and different types of data, then this book is for you. The only thing you need is a basic understanding of what Business Intelligence is and data concepts.

If you have C# knowledge but now want to become truly confident in creating fully functional 2D RPG games with Unity, then this book will show you everything you need to know.

Step-by-step recipes filled with practical code samples and engaging examples demonstrate Haskell in practice, and then the concepts behind the code. This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed.

This book is built on recipes written in an easy-to-follow manner accompanied by diagrams and crucial insights and knowledge on what they mean in the real world. This book is ideal for musicians and producers who want to take their music creation skills to the next level, learn tips and tricks, and understand the key elements and nuances in building inspirational music. It’s good to have some knowledge about music production, but if you have creativity and a good pair of ears, you are already ahead of the curve and well on your way.

This book provides an overview of the kill chain approach to penetration testing, and then focuses on using Kali Linux to provide examples of how this methodology is applied in the real world. After describing the underlying concepts, step-by-step examples are provided that use selected tools to demonstrate the techniques.If you are an IT professional or a security consultant who wants to maximize the success of your network testing using some of the advanced features of Kali Linux, then this book is for you. This book will teach you how to become an expert in the pre-engagement, management, and documentation of penetration testing by building on your understanding of Kali Linux and wireless concepts.

This book is written in a practical and friendly style with practical tutorials, exercises, and detailed images which will help you master the third dimension. This book is intended for everyone who wants to create accurate 3D models in AutoCAD, like architecture, engineering, or design professionals, and students. Only basic understanding of 2D AutoCAD is needed.

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.

A comprehensive practical guide that walks you through the multiple stages of data management in enterprise and gives you numerous design patterns with appropriate code examples to solve frequent problems in each of these stages. The chapters are organized to mimick the sequential data flow evidenced in Analytics platforms, but they can also be read independently to solve a particular group of problems in the Big Data life cycle. If you are an experienced developer who is already familiar with Pig and is looking for a use case standpoint where they can relate to the problems of data ingestion, profiling, cleansing, transforming, and egressing data encountered in the enterprises. Knowledge of Hadoop and Pig is necessary for readers to grasp the intricacies of Pig design patterns better.

This book is written in an easytounderstand style, following an enterprise development process through all the phases of development and deployment. Concepts are illustrated with realworld examples and the methods used are explained stepbystep. This book is for Oracle developers looking to start using Oracle’s latest development tool and J2EE developers looking for a more productive way to build modern web applications. This book will guide you through the creation of a successful enterprise application with Oracle ADF 12c, and therefore it assumes you have basic knowledge of Java, JDeveloper, and databases.

Create robust and maintainable Java applications using the functional style of programmingAbout This BookExplore how you can blend object-oriented and functional programming styles in JavaUse lambda expressions to write flexible and succinct codeA tutorial that strengthens your fundamentals in functional programming techniques to enhance your applications Who This Book Is For If you are a Java developer with object-oriented experience and want to use a functional programming approach in your applications, then this book is for you. All you need to get started is familiarity with basic Java object-oriented programming concepts.What You Will LearnUse lambda expressions to simplyfy codeUse function composition to achieve code fluencyApply streams to simply implementations and achieve parallelismIncorporate recursion to support an application’s functionalityProvide more robust implementations using OptionalsImplement design patterns with less codeRefactor object-oriented code to create a functional solutionUse debugging and testing techniques specific to functional programs In Detail Functional programming is an increasingly popular technology that allows you to simplify many tasks that are often cumbersome and awkward using an object-oriented approach. It is important to understand this approach and know how and when to apply it. Functional programming requires a different mindset, but once mastered it can be very rewarding. This book simplifies the learning process as a problem is described followed by its implementation using an object-oriented approach and then a solution is provided using appropriate functional programming techniques. Writing succinct and maintainable code is facilitated by many functional programming techniques including lambda expressions and streams. In this book, you will see numerous examples of how these techniques can be applied starting with an introduction to lambda expressions. Next, you will see how they can replace older approaches and be combined to achieve surprisingly elegant solutions to problems. This is followed by the investigation of related concepts such as the Optional class and monads, which offer an additional approach to handle problems. Design patterns have been instrumental in solving common problems. You will learn how these are enhanced with functional techniques. To transition from an object-oriented approach to a functional one, it is useful to have IDE support. IDE tools to refactor, debug, and test functional programs are demonstrated through the chapters. The end of the book brings together many of these functional programming techniques to create a more comprehensive application. You will find this book a very useful resource to learn and apply functional programming techniques in Java.Style and approach In this tutorial, each chapter starts with an introduction to the terms and concepts covered in that chapter. It quickly progresses to contrast an object-oriented approach with a functional approach using numerous code examples.

Covering SQL Developer fundamentals as well more intermediate and advanced topics, this book uses in-depth explanation and detailed examples to help you get the most out of Oracle SQL Developer. The book has a modular structure, so that you can dip into any chapter that covers your current area of focus and get going. This book is for Oracle developers who want to ease their database development, and enhance their productivity using Oracle SQL Developer. You should have a programming knowledge of SQL and PL/SQL, and a general familiarity with Oracle database concepts.

This book is a hands-on tutorial detailing Oracle Enterprise Manager Grid Control's management of Middleware. It is a 'how-to', and provides best practices, tips, and troubleshooting guidelines for managing middleware with Oracle Enterprise Manager. This book is targeted at Middleware Administrators, IT Architects, and System Administrators who want to monitor, diagnose, and maximize the system performance of Oracle [if gte mso 9] Normal 0 false false false EN-US X-NONE X-NONE ![endif]--[if gte mso 9] ![endif] Fusion Middleware solutions. The book assumes basic knowledge of middleware/application server management. It can also be used by Database Administrators who want to become Middleware Administrators.

This is a practical book with step-by-step guidelines to integrate Silverlight 4 applications in a SharePoint 2010 Server environment. This book focuses on the integration of the two technologies and is not a primer for any of the individual technologies. It offers clear examples to successfully perform the most important integration tasks. If you are an application developer who wants to implement Silverlight 4 applications within a SharePoint 2010 environment, this book is for you. We assume that the reader has prior knowledge of Silverlight and SharePoint 2010 and this book focuses more on the integration of Silverlight with SharePoint 2010.

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.

If you are a developer who implements ElasticSearch in your web applications and want to sharpen your understanding of the core elements and applications, this is the book for you. It is assumed that you’ve got working knowledge of JSON and, if you want to extend ElasticSearch, of Java and related technologies.

Master machine learning techniques with R to deliver insights for complex projectsAbout This BookGet to grips with the application of Machine Learning methods using an extensive set of R packagesUnderstand the benefits and potential pitfalls of using machine learning methodsImplement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will LearnGain deep insights to learn the applications of machine learning tools to the industryManipulate data in R efficiently to prepare it for analysisMaster the skill of recognizing techniques for effective visualization of dataUnderstand why and how to create test and training data sets for analysisFamiliarize yourself with fundamental learning methods such as linear and logistic regressionComprehend advanced learning methods such as support vector machinesRealize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.