Leverage the power of Scala with different tools to build scalable, robust data science applicationsAbout This BookA complete guide for scalable data science solutions, from data ingestion to data visualizationDeploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizationsBuild functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples providedWho This Book Is ForIf you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions.What You Will LearnTransform and filter tabular data to extract features for machine learningImplement your own algorithms or take advantage of MLLib’s extensive suite of models to build distributed machine learning pipelinesRead, transform, and write data to both SQL and NoSQL databases in a functional mannerWrite robust routines to query web APIsRead data from web APIs such as the GitHub or Twitter APIUse Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirementsCreate Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizationsDeploy scalable parallel applications using Apache Spark, loading data from HDFS or HiveIn DetailScala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and *ing language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines.This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala.Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala’s emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks.This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.Style and approachA tutorial with complete examples, this book will give you the tools to start building useful data engineering and data science solutions straightaway

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.

Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book ? Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. ? Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and "dirty" real-world data. ? Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn ? Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL ? Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB ? Perform data quality checks, data visualization, and basic statistical analysis tasks ? Perform data munging tasks on publically available datasets ? Learn how to use Spark SQL and Apache Kafka to build streaming applications ? Learn key performance-tuning tips and tricks in Spark SQL applications ? Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project. Style and approach This book is a hands-on guide to designing, building, and deploying Spark SQL-centric production applications at scale.

More than 80 recipes to help you leverage the various extensibility features available for Microsoft Dynamics and solve problems easily About This Book ? Customize, configure, and extend the vanilla features of Dynamics 365 to deliver bespoke CRM solutions fit for any organization ? Implement business logic using point-and-click configuration, plugins, and client-side *s with MS Dynamics 365 ? Built a DevOps pipeline as well as Integrate Dynamics 365 with Azure and other platforms Who This Book Is For This book is for developers, administrators, consultants, and power users who want to learn about best practices when extending Dynamics 365 for enterprises. You are expected to have a basic understand of the Dynamics CRM/365 platform. What You Will Learn ? Customize, configure, and extend Microsoft Dynamics 365 ? Create business process automation ? Develop client-side extensions to add features to the Dynamics 365 user interface ? Set up a security model to securely manage data with Dynamics 365 ? Develop and deploy clean code plugins to implement a wide range of custom behaviors ? Use third-party applications, tools, and patterns to integrate Dynamics 365 with other platforms ? Integrate with Azure, Java, SSIS, PowerBI, and Octopus Deploy ? Build an end-to-end DevOps pipeline for Dynamics 365 In Detail Microsoft Dynamics 365 is a powerful tool. It has many unique features that empower organisations to bridge common business challenges and technology pitfalls that would usually hinder the adoption of a CRM solution. This book sets out to enable you to harness the power of Dynamics 365 and cater to your unique circumstances. We start this book with a no-code configuration chapter and explain the schema, fields, and forms modeling techniques. We then move on to server-side and client-side custom code extensions. Next, you will see how best to integrate Dynamics 365 in a DevOps pipeline to package and deploy your extensions to the various SDLC environments. This book also covers modern libraries and integration patterns that can be used with Dynamics 365 (Angular, 3 tiers, and many others). Finally, we end by highlighting some of the powerful extensions available. Throughout we explain a range of design patterns and techniques that can be used to enhance your code quality; the aim is that you will learn to write enterprise-scale quality code. Style and approach This book takes a recipe-based approach, delivering practical examples and use cases so that you can identify the best possible approach to extend your Dynamics 365 deployment and tackle your specific business problems.

Incorporate the power of Einstein in your Salesforce application About This Book ? Make better predictions of your business processes using prediction and predictive modeling ? Build your own custom models by leveraging PredictionIO on the Heroku platform ? Integrate Einstein into various cloud services to predict sales, marketing leads, insights into news feeds, and more Who This Book Is For This book is for developers, data scientists, and Salesforce-experienced consultants who want to explore Salesforce Einstein and its current offerings. It assumes some prior experience with the Salesforce platform. What You Will Learn ? Get introduced to AI and its role in CRM and cloud applications ? Understand how Einstein works for the sales, service, marketing, community, and commerce clouds ? Gain a deep understanding of how to use Einstein for the analytics cloud ? Build predictive apps on Heroku using PredictionIO, and work with Einstein Predictive Vision Services ? Incorporate Einstein in the IoT cloud ? Test the accuracy of Einstein through Salesforce reporting and Wave analytics In Detail Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the force.com platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce’s various cloud offerings and how they can use Einstein’s capabilities and enhance applications. Style and approach This book takes a straightforward approach to explain Salesforce Einstein and all of its potential applications. Filled with examples, the book presents the facts along with seasoned advice and real-world use cases to ensure you have all the resources you need to incorporate the power of Einstein in your work.

This cookbook has recipes written in simple, easy to understand format with lots of screenshots and insightful tips and hints. If you are an Oracle Database Administrator, Security Manager or Security Auditor looking to secure the Oracle Database or prevent it from being hacked, then this book is for you. This book assumes you have a basic understanding of security concepts.

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.

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.

vSphere High Performance Cookbook is written in a practical, helpful style with numerous recipes focusing on answering and providing solutions to common, and not-so common, performance issues and problems.The book is primarily written for technical professionals with system administration skills and some VMware experience who wish to learn about advanced optimization and the configuration features and functions for vSphere 5.1.

A practical guide which will help to discover how to setup and configure the Salesforce CRM application. It offers solutions and practical examples on how to further improve and maintain its functionality with clear systematic instructions. Being highly organized and compact, this book contains detailed instructions with screenshots, diagrams, and tips that clearly describe how you can administer and configure complex Salesforce CRM functionality with absolute ease.This book is for administrators who want to develop and strengthen their Salesforce CRM skills in the areas of configuration and system management. Whether you are a novice or a more experienced admin, this book aims to enhance your knowledge and understanding of the Salesforce CRM platform and by the end of the book, you should be ready to administer Salesforce CRM in a real-world environment.

This book focuses on readers starting their journey with Hyper-V, and assumes they have minimal or no knowledge of virtualization.

This book will help beginners to create stylish and professional looking dashboards in no time. It is also intended for BI developers who want to use SAP BO to facilitate BI in their organizations. No prior knowledge is required, however, you must have a basic knowledge of MS Excel and some analytical skills to build expressive business charts.

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

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.

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 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.

You will be led carefully stepbystep through a detailed set of recipes. This book focuses on web content management using Microsoft SharePoint 2013 server. The practical examples are built logically throughout the chapters to create a common theme. This book is ideal for developers who want to broaden their understanding of the web content management features available with SharePoint 2013. It is assumed that you already have some experience using SharePoint and developing web content. Experience with Microsoft PowerShell and coding C# with Visual Studio will also be helpful, but is not essential.

Throughout the book, we will follow a fictional company, the case study will help you in implementing FIM 2010 R2. All the examples in the book will relate to this fictive company and you will be taken from design, to installation, to configuration of FIM 2010 R2. If you are implementing and managing FIM 2010 R2 in your business, then this book is for you. You will need to have a basic understanding of Microsoft based infrastructure using Active Directory. If you are new to Forefront Identity Management, the case-study approach of this book will help you to understand the concepts and implement them.