If you are a Python developer who wants to master the world of data science, then this book is for you. Some knowledge of data science is assumed.

This easy-to-understand tutorial covers Oracle Warehouse Builder from the ground up, and taps into the author's wide experience as a software and database engineer. Written in a relaxed style with step-by-step explanations, lots of screenshots are provided throughout the book. There are numerous tips and helpful hints throughout that are not found in the original documentation. By following this book, you can use Oracle Warehouse Builder in the best possible way and maximize your learning potential. This book is a good starting point for database engineers, administrators, and architects who are responsible for data warehouse projects and need to design them and load data into them. If you are someone who wants to learn Oracle Warehouse Builder and expand your knowledge of the tool and data warehousing, this is an ideal book for you. No prior data warehouse or database experience is presumed with all new database and data warehouse technical terms and concepts explained in clear easy-to-understand language.

This Cookbook contains step-by-step instructions for Report Studio 10.1 users to author effective reports. The book is designed in a way that you can refer to it chapter by chapter, look at the list of recipes and read them in no particular order.The Cognos 10.1 Report Studio Cookbook is for you if you are a Business Intelligence Developer who is working on IBM Cognos 10 Report Studio and wants to author impressive reports by putting to use what this tool has to offer. It is also ideal you are a Business Analyst or Power User who authors his own reports and wants to look beyond the conventional features of IBM Cognos 10 Report Studio.This book assumes that you are familiar with the architecture of IBM Cognos 10. You should also have basic knowledge of IBM Cognos Report Studio and can do the basic report authoring tasks.

Written in the style of a cookbook. Microsoft Dynamics NAV 7 Programming Cookbook is full of recipes to help you get the job done.If you are a junior / entry-level NAV developer then the first half of the book is designed primarily for you. You may or may not have any experience programming. It focuses on the basics of NAV programming.If you are a mid-level NAV developer, you will find these chapters explain how to think outside of the NAV box when building solutions. There are also recipes that senior developers will find useful.

Explore the capabilities of Dynamics NAV 2016 and discover all you need to implement it About This Book Learn the key roles of your Dynamics NAV partner and the roles within your customer’s organization Create configuration packages and perform data migration on your own Find out how to troubleshoot your problems effectively with your Dynamics NAV partner Who This Book Is For This book is for Dynamics NAV partners and end users who want to know everything about Dynamics NAV implementations. It is aimed at those who want to be project managers or get involved with Dynamics NAV, but do not have the expertise to write code themselves. What You Will Learn Study the roles within a Dynamics NAV partner and within a customer’s company Create reusable data migration packages Work with the debugger to pinpoint error messages Get to grips with the key tables used in data reporting and analysis Successfully upgrade your installation to the latest version Manage and expand your existing installation with additional functionalities Explore the free third-party add-ons that can leverage your existing installation In Detail Microsoft Dynamics NAV 2016 is an Enterprise Resource Planning (ERP) application used in all kinds of organizations around the world. It provides a great variety of functionality out-of-the-box in different topics such as accounting, sales, purchase processing, logistics, or manufacturing. It also allows companies to grow the application by customizing the solution to meet specific requirements. This book is a hands-on tutorial on working with a real Dynamics NAV implementation. You will learn about the team from your Microsoft Dynamics NAV partner as well as the team within the customer’s company. This book provides an insight into the different tools available to migrate data from the client’s legacy system into Microsoft Dynamics NAV. If you are already live with Microsoft Dynamics NAV, this books talks about upgrades and what to expect from them. We’ll also show you how to implement additional or expanding functionalities within your existing Microsoft Dynamics NAV installation, perform data analysis, debug error messages, and implement free third-party add-ons to your existing installation. This book will empower you with all the skills and knowledge you need for a successful implementation. Style and approach This book is step-by-step guide to implementing Dynamics NAV from start to finish.

Install, configure, and support your XenApp systems with the power of Citrix XenAppAbout This BookFamiliarize yourself with Citrix applications and desktop virtualizationMaintain and troubleshoot your XenApp environment to minimize system downtimeA hands-on, step-by-step guide with a practical approach and real-world examples to get you up and running with XenApp systemsWho This Book Is ForThis book is intended for IT administrators and consultants who want to build application and desktop virtualization solutions for their employers and customers. No prior knowledge of Citrix technologies is required.What You Will LearnMake the use case for Citrix XenApp and design your first systemPrepare your existing IT infrastructure for XenApp and learn what licenses you needInstall and configure the XenApp infrastructureEnable access with StoreFront and NetScaler GatewayEnable load balancing with NetScalerMaintain servers and publish applications and desktopsManage printing in a Citrix environmentTroubleshoot your environment using advanced tools and methodologies employed by Citrix Escalation TeamsIn DetailIf you want to effectively deploy the various components of Citrix XenApp to create an enterprise environment for application and desktop delivery, this hands-on guide is perfect for you. You start off by understanding the need and benefits of Citrix XenApp with respect to Virtualization technology. After this, you will get to grips with the requirement analysis and designing aspect of building XenApp systems and all the necessary installation and configuration procedures for Citrix XenApp, StoreFront and NetScalar Gateway are explained one by one in detail.Step-by-step, you will learn to deploy your first XenApp with the Machine Creation Services method and Provisioning Services method. After this, you will explore the administering part of applications and systems, followed by printing in the XenApp environment. Next, you will learn all the trips and tricks required to troubleshoot and support the XenApp environment. By the end of this book, you will be ready to go live with your new XenApp environment.Style and approachThis is a step-by-step guide to technical implementations in a conversational and easy-to-follow style. Each component is deployed sequentially until a full solution is built. Basic as well as advanced features of the product are explored to appeal to the widest possible audience interested in the topic.

Write efficient, clean, and reusable code with ScalaAbout This BookUnleash the power of Scala and apply it in the real worldIncrease your efficiency by leveraging the power of Creational, Structural, Behavioural, and Functional design patternsBuild object oriented and functional applications quickly and effectivelyWho This Book Is ForIf you want to increase your understanding of Scala and apply it to real-life application development, then this book is for you. We’ve also designed the book to be used as a quick reference guide while creating applications. Previous Scala programming knowledge is expected.What You Will LearnImmerse yourself in industry-standard design patterns—structural, creational, and behavioral—to create extraordinary applicationsFeel the power of traits and their application in ScalaImplement abstract and self types and build clean design patternsBuild complex entity relationships using structural design patternsCreate applications faster by applying functional design patternsIn DetailScala has become increasingly popular in many different IT sectors. The language is exceptionally feature-rich which helps developers write less code and get faster results. Design patterns make developer’s lives easier by helping them write great software that is easy to maintain, runs efficiently and is valuable to the company or people concerned.You will learn about the various features of Scala and be able to apply well-known, industry-proven design patterns in your work. The book starts off by focusing on some of the most interesting features of Scala while using practical real-world examples. We will also cover the popular "Gang of Four" design patterns and show you how to incorporate functional patterns effectively. By the end of this book, you will have enough knowledge and understanding to quickly assess problems and come up with elegant solutions.Style and approachThe design patterns in the book will be explained using real-world, step-by-step examples. For each design pattern, there will be hints about when to use it and when to look for something more suitable. This book can also be used as a practical guide, showing you how to leverage design patterns effectively.

Secure your Oracle Database 12c with this valuable Oracle support resource, featuring more than 100 solutions to the challenges of protecting your data About This Book Explore and learn the new security features introduced in Oracle Database 12c, to successfully secure your sensitive data Learn how to identify which security strategy is right for your needs – and how to apply it Each ‘recipe’ provides you with a single step-by-step solution, making this book a vital resource, delivering Oracle support in one accessible place Who This Book Is For This book is for DBAs, developers, and architects who are keen to know more about security in Oracle Database 12c. This book is best suited for beginners and intermediate-level database security practitioners. Basic knowledge of Oracle Database is expected, but no prior experience of securing a database is required. What You Will Learn Analyze application privileges and reduce the attack surface Reduce the risk of data exposure by using Oracle Data Redaction and Virtual Private Database Control data access and integrity in your organization using the appropriate database feature or option Learn how to protect your databases against application bypasses Audit user activity using the new auditing architecture Restrict highly privileged users from accessing data Encrypt data in Oracle Database Work in a real-world environment where a multi-layer security strategy is applied In Detail Businesses around the world are paying much greater attention toward database security than they ever have before. Not only does the current regulatory environment require tight security, particularly when dealing with sensitive and personal data, data is also arguably a company’s most valuable asset - why wouldn’t you want to protect it in a secure and reliable databaseOracle Database lets you do exactly that. It’s why it is one of the world’s leading databases – with a rich portfolio of features to protect data from contemporary vulnerabilities, it’s the go-to database for many organizations. Oracle Database 12c Security Cookbook helps DBAs, developers, and architects to better understand database security challenges. Let it guide you through the process of implementing appropriate security mechanisms, helping you to ensure you are taking proactive steps to keep your data safe. Featuring solutions for common security problems in the new Oracle Database 12c, with this book you can be confident about securing your database from a range of different threats and problems. Style and approach Each chapter explains the different aspects of security through a series of recipes. Each recipe presents instructions in a step-by-step manner, supported by explanations of the topic.

Over 170 advanced recipes to search, analyze, deploy, manage, and monitor data effectively with Elasticsearch 5.x About This Book Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies Write native plugins to extend the functionalities of Elasticsearch 5.x to boost your business Packed with clear, step-by-step recipes to walk you through the capabilities of Elasticsearch 5.x Who This Book Is For If you are a developer who wants to get the most out of Elasticsearch for advanced search and analytics, this is the book for you. Some understanding of JSON is expected. If you want to extend Elasticsearch, understanding of Java and related technologies is also required. What You Will Learn Choose the best Elasticsearch cloud topology to deploy and power it up with external plugins Develop tailored mapping to take full control of index steps Build complex queries through managing indices and documents Optimize search results through executing analytics aggregations Monitor the performance of the cluster and nodes Install Kibana to monitor cluster and extend Kibana for plugins Integrate Elasticsearch in Java, Scala, Python and Big Data applications In Detail Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and *ing. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch. Style and approach This book follows a problem-solution approach to effectively use and manage Elasticsearch. Each recipe focuses on a particular task at hand, and is explained in a very simple, easy to understand manner.

Get the most out of the Elastic Stack for various complex analytics using this comprehensive and practical guide About This Book Your one-stop solution to perform advanced analytics with Elasticsearch, Logstash, and Kibana Learn how to make better sense of your data by searching, analyzing, and logging data in a systematic way This highly practical guide takes you through an advanced implementation on the ELK stack in your enterprise environment Who This Book Is For This book cater to developers using the Elastic stack in their day-to-day work who are familiar with the basics of Elasticsearch, Logstash, and Kibana, and now want to become an expert at using the Elastic stack for data analytics. What You Will Learn Build a pipeline with help of Logstash and Beats to visualize Elasticsearch data in Kibana Use Beats to ship any type of data to the Elastic stack Understand Elasticsearch APIs, modules, and other advanced concepts Explore Logstash and it’s plugins Discover how to utilize the new Kibana UI for advanced analytics See how to work with the Elastic Stack using other advanced configurations Customize the Elastic Stack and plugin development for each of the component Work with the Elastic Stack in a production environment Explore the various components of X-Pack in detail. In Detail Even structured data is useless if it can’t help you to take strategic decisions and improve existing system. If you love to play with data, or your job requires you to process custom log formats, design a scalable analysis system, and manage logs to do real-time data analysis, this book is your one-stop solution. By combining the massively popular Elasticsearch, Logstash, Beats, and Kibana, elastic.co has advanced the end-to-end stack that delivers actionable insights in real time from almost any type of structured or unstructured data source. If your job requires you to process custom log formats, design a scalable analysis system, explore a variety of data, and manage logs, this book is your one-stop solution. You will learn how to create real-time dashboards and how to manage the life cycle of logs in detail through real-life scenarios. This book brushes up your basic knowledge on implementing the Elastic Stack and then dives deeper into complex and advanced implementations of the Elastic Stack. We’ll help you to solve data analytics challenges using the Elastic Stack and provide practical steps on centralized logging and real-time analytics with the Elastic Stack in production. You will get to grip with advanced techniques for log analysis and visualization. Newly announced features such as Beats and X-Pack are also covered in detail with examples. Toward the end, you will see how to use the Elastic stack for real-world case studies and we’ll show you some best practices and troubleshooting techniques for the Elastic Stack. Style and approach This practical guide shows you how to perform advanced analytics with the Elastic stack through real-world use cases. It includes common and some not so common scenarios to use the Elastic stack for data analysis.

Over 70 practical recipes to analyze multi-dimensional data in SQL Server 2016 Analysis Services cubes About This Book Updated for SQL Server 2016, this book helps you take advantage of the new MDX commands and the new features introduced in SSAS Perform time-related, context-aware, and business related-calculations with ease to enrich your Business Intelligence solutions Collection of techniques to write flexible and high performing MDX queries in SSAS with carefully structured examples Who This Book Is For This book is for anyone who has been involved in working with multidimensional data. If you are a multidimensional cube developer, a multidimensional database administrator, or a report developer who writes MDX queries to access multidimensional cube, this book will help you. If you are a power cube user or an experienced business analyst, you will also find this book invaluable in your data analysis. This book is for you are interested in doing more data analysis so that the management can make timely and accurate business decisions. What You Will Learn Grasp the fundamental MDX concepts, features, and techniques Work with sets Work with Time dimension and create time-aware calculations Make analytical reports compact, concise, and efficient Navigate cubes Master MDX for reporting with Reporting Services (new) Perform business analytics Design efficient cubes and efficient MDX queries Create metadata-driven calculations (new) Capture MDX queries and many other techniques In Detail If you're often faced with MDX challenges, this is a book for you. It will teach you how to solve various real-world business requirements using MDX queries and calculations. Examples in the book introduce an idea or a problem and then guide you through the process of implementing the solution in a step-by-step manner, inform you about the best practices and offer a deep knowledge in terms of how the solution works. Recipes are organized by chapters, each covering a single topic. They start slowly and logically progress to more advanced techniques. In case of complexity, things are broken down. Instead of one, there are series of recipes built one on top of another. This way you are able to see intermediate results and debug potential errors faster. Finally, the cookbook format is here to help you quickly identify the topic of interest and in it a wide range of practical solutions, that is – MDX recipes for your success. Style and approach This book is written in a cookbook format, where you can browse through and look for solutions to a particular problem in one place. Each recipe is short, to the point and grouped by relevancy. All the recipes are sequenced in a logical progression; you will be able to build up your understanding of the topic incrementally.

Create interactive cross-platform reports and dashboards using SQL Server 2016 Reporting Services About This Book Get up to speed with the newly-introduced enhancements and the more advanced query and reporting features Easily access your important data by creating visually appealing dashboards in the Power BI practical recipe Create cross-browser and cross-platform reports using SQL Server 2016 Reporting Services Who This Book Is For This book is for software professionals who develop and implement reporting solutions using Microsoft SQL Server. It is especially relevant for professionals who are software engineers, software architects, DW/BI engineers, and DW/BI architects who perform simple to complex report authoring implementations. This book is also suitable for those who develop software solutions that integrate reporting solutions and are keen to learn about Microsoft SQL Server 2016’s features and capabilities. What You Will Learn Key capabilities, architecture, and components of Reporting Services New features that have been added to Reporting Services Design the architecture for reporting solutions Design the architecture for BI solutions Implement reporting solutions using Reporting Services Improve the performance, availability, and scalability of the reporting solution Enhance reporting solutions with custom programming and improved security In Detail Microsoft SQL Server 2016 Reporting Services comes with many new features. It offers different types of reporting such as Production, Ad-hoc, Dashboard, Mash-up, and Analytical. SQL Server 2016 also has a surfeit of new features including Mobile Reporting, and Power BI integration. This book contains recipes that explore the new and advanced features added to SQL Server 2016. The first few chapters cover recipes on configuring components and how to explore these new features. You’ll learn to build your own reporting solution with data tools and report builder, along with learning techniques to create visually appealing reports. This book also has recipes for enhanced mobile reporting solutions, accessing these solutions effectively, and delivering interactive business intelligence solutions. Towards the end of the book, you’ll get to grips with running reporting services in SharePoint integrated mode and be able to administer, monitor, and secure your reporting solution. This book covers about the new offerings of Microsoft SQL Server 2016 Reporting Services in comprehensive detail and uses examples of real-world problem-solving business scenarios. Style and approach This comprehensive cookbook follows a problem-solution approach to help you overcome any obstacle when creating interactive, visually-appealing reports using SQL Server 2016 Reporting Services. Each recipe focuses on a specific task and is written in a clear, solution-focused style.

"Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book ?Explore and create intelligent systems using cutting-edge deep learning techniques ?Implement deep learning algorithms and work with revolutionary libraries in Python ?Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and more Who This Book Is For This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired. What You Will Learn ?Get a practical deep dive into deep learning algorithms ?Explore deep learning further with Theano, Caffe, Keras, and TensorFlow ?Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines ?Dive into Deep Belief Nets and Deep Neural Networks ?Discover more deep learning algorithms with Dropout and Convolutional Neural Networks ?Get to know device strategies so you can use deep learning algorithms and libraries in the real world In Detail With an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries. The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results. Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques. Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside. Style and approach Python Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects. "

Master the principles and techniques of multithreaded programming with the Java 8 Concurrency APIAbout This BookImplement concurrent applications using the Java 8 Concurrency API and its new componentsImprove the performance of your applications or process more data at the same time, taking advantage of all of your resources.Construct real-world examples related to machine learning, data mining, image processing, and client/server environmentsWho This Book Is ForIf you are a competent Java developer with a good understanding of concurrency but have no knowledge of how to effectively implement concurrent programs or use streams to make processes more efficient, then this book is for you.What You Will LearnDesign concurrent applications by converting a sequential algorithm into a concurrent oneDiscover how to avoid all the possible problems you can get in concurrent algorithmsUse the Executor framework to manage concurrent tasks without creating threadsExtend and modify Executors to adapt their behavior to your needsSolve problems using the divide and conquer technique and the Fork/Join frameworkProcess massive data sets with parallel streams and Map/Reduce implementationControl data-race conditions using concurrent data structures and synchronization mechanismsTest and monitor concurrent applicationsIn DetailConcurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. All the sub-tasks are combined together once the required results are achieved; they are then merged to get the final output. The whole process is very complex. This process goes from the design of concurrent algorithms to the testing phase where concurrent applications need extra attention. Java includes a comprehensive API with a lot of ready-to-use components to implement powerful concurrency applications in an easy way, but with a high flexibility to adapt these components to your needs.The book starts with a full de*ion of design principles of concurrent applications and how to parallelize a sequential algorithm. We'll show you how to use all the components of the Java Concurrency API from basics to the most advanced techniques to implement them in powerful concurrency applications in Java.You will be using real-world examples of complex algorithms related to machine learning, data mining, natural language processing, image processing in client / server environments. Next, you will learn how to use the most important components of the Java 8 Concurrency API: the Executor framework to execute multiple tasks in your applications, the phaser class to implement concurrent tasks divided into phases, and the Fork/Join framework to implement concurrent tasks that can be split into smaller problems (using the divide and conquer technique). Toward the end, we will cover the new inclusions in Java 8 API, the Map and Reduce model, and the Map and Collect model. The book will also teach you about the data structures and synchronization utilities to avoid data-race conditions and other critical problems. Finally, the book ends with a detailed de*ion of the tools and techniques that you can use to test a Java concurrent application.Style and approach A complete guide implementing real-world examples with algorithms related to machine learning, data mining, and natural language processing in client/server environments. All the examples are explained in a step-by-step approach.

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.

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

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.

Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R’s advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R’s range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

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 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.