Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Price Forecasting Models For Hortonworks Inc Hdp Stock
Download Price Forecasting Models For Hortonworks Inc Hdp Stock full books in PDF, epub, and Kindle. Read online Price Forecasting Models For Hortonworks Inc Hdp Stock ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Microsoft Azure Essentials - Fundamentals of Azure by : Michael Collier
Download or read book Microsoft Azure Essentials - Fundamentals of Azure written by Michael Collier and published by Microsoft Press. This book was released on 2015-01-29 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. The first ebook in the series, Microsoft Azure Essentials: Fundamentals of Azure, introduces developers and IT professionals to the wide range of capabilities in Azure. The authors - both Microsoft MVPs in Azure - present both conceptual and how-to content for key areas, including: Azure Websites and Azure Cloud Services Azure Virtual Machines Azure Storage Azure Virtual Networks Databases Azure Active Directory Management tools Business scenarios Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the “Microsoft Azure Essentials” series.
Book Synopsis AI and Big Data on IBM Power Systems Servers by : Scott Vetter
Download or read book AI and Big Data on IBM Power Systems Servers written by Scott Vetter and published by IBM Redbooks. This book was released on 2019-04-10 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments. In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including: IBM Watson Machine Learning Accelerator (see note for product naming) IBM Watson Studio Local IBM Power SystemsTM IBM SpectrumTM Scale IBM Data Science Experience (IBM DSX) IBM Elastic StorageTM Server Hortonworks Data Platform (HDP) Hortonworks DataFlow (HDF) H2O Driverless AI We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security. Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise. Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names.
Book Synopsis Practical Data Science with Hadoop and Spark by : Ofer Mendelevitch
Download or read book Practical Data Science with Hadoop and Spark written by Ofer Mendelevitch and published by Addison-Wesley Professional. This book was released on 2016-12-08 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language
Book Synopsis Apache Hadoop 3 Quick Start Guide by : Hrishikesh Vijay Karambelkar
Download or read book Apache Hadoop 3 Quick Start Guide written by Hrishikesh Vijay Karambelkar and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fast paced guide that will help you learn about Apache Hadoop 3 and its ecosystem Key FeaturesSet up, configure and get started with Hadoop to get useful insights from large data setsWork with the different components of Hadoop such as MapReduce, HDFS and YARN Learn about the new features introduced in Hadoop 3Book Description Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster. What you will learnStore and analyze data at scale using HDFS, MapReduce and YARNInstall and configure Hadoop 3 in different modesUse Yarn effectively to run different applications on Hadoop based platformUnderstand and monitor how Hadoop cluster is managedConsume streaming data using Storm, and then analyze it using SparkExplore Apache Hadoop ecosystem components, such as Flume, Sqoop, HBase, Hive, and KafkaWho this book is for Aspiring Big Data professionals who want to learn the essentials of Hadoop 3 will find this book to be useful. Existing Hadoop users who want to get up to speed with the new features introduced in Hadoop 3 will also benefit from this book. Having knowledge of Java programming will be an added advantage.
Book Synopsis Machine Learning and Metaheuristics Algorithms, and Applications by : Sabu M. Thampi
Download or read book Machine Learning and Metaheuristics Algorithms, and Applications written by Sabu M. Thampi and published by Springer Nature. This book was released on 2020-04-04 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2019, held in Trivandrum, India, in December 2019. The 17 full papers and 6 short papers presented in this volume were thoroughly reviewed and selected from 53 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc.
Book Synopsis Big Data For Dummies by : Judith S. Hurwitz
Download or read book Big Data For Dummies written by Judith S. Hurwitz and published by John Wiley & Sons. This book was released on 2013-04-02 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.
Book Synopsis Introducing Microsoft SQL Server 2016 by : Stacia Varga
Download or read book Introducing Microsoft SQL Server 2016 written by Stacia Varga and published by Microsoft Press. This book was released on 2016-06-28 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: With Microsoft SQL Server 2016, a variety of new features and enhancements to the data platform deliver breakthrough performance, advanced security, and richer, integrated reporting and analytics capabilities. In this ebook, we introduce new security features: Always Encrypted, Row-Level Security, and dynamic data masking; discuss enhancements that enable you to better manage performance and storage: TemDB configuration, query store, and Stretch Database; review several improvements to Reporting Services; and also describe AlwaysOn Availability Groups, tabular enhancements, and R integration.
Book Synopsis IBM Software-Defined Storage Guide by : Larry Coyne
Download or read book IBM Software-Defined Storage Guide written by Larry Coyne and published by IBM Redbooks. This book was released on 2018-07-21 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, new business models in the marketplace coexist with traditional ones and their well-established IT architectures. They generate new business needs and new IT requirements that can only be satisfied by new service models and new technological approaches. These changes are reshaping traditional IT concepts. Cloud in its three main variants (Public, Hybrid, and Private) represents the major and most viable answer to those IT requirements, and software-defined infrastructure (SDI) is its major technological enabler. IBM® technology, with its rich and complete set of storage hardware and software products, supports SDI both in an open standard framework and in other vendors' environments. IBM services are able to deliver solutions to the customers with their extensive knowledge of the topic and the experiences gained in partnership with clients. This IBM RedpaperTM publication focuses on software-defined storage (SDS) and IBM Storage Systems product offerings for software-defined environments (SDEs). It also provides use case examples across various industries that cover different client needs, proposed solutions, and results. This paper can help you to understand current organizational capabilities and challenges, and to identify specific business objectives to be achieved by implementing an SDS solution in your enterprise.
Book Synopsis Data Analytics for Intelligent Transportation Systems by : Mashrur Chowdhury
Download or read book Data Analytics for Intelligent Transportation Systems written by Mashrur Chowdhury and published by Elsevier. This book was released on 2024-11-02 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics
Book Synopsis Capital Compounders by : Robin Speziale
Download or read book Capital Compounders written by Robin Speziale and published by Robin R. Speziale. This book was released on 2018-10-19 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: FROM NATIONAL BESTSELLING AUTHOR ROBIN R. SPEZIALE – LEARN HOW TO MAKE MONEY INVESTING IN GROWTH STOCKS In Capital Compounders, DIY Investor & National Bestselling Author Robin R. Speziale makes it easy for anyone to beat the market and make money investing in growth stocks! Robin R. Speziale shares his journey building a $300,000+ stock portfolio before 30 (and how you can too!) by investing in growth stocks or “Capital Compounders” – stocks that double, and then double again, and again on the market. Capital Compounder stocks have achieved the “tenbagger” ($1 turns into $10), and some even the “100-bagger” ($1 turns into $100) status. Mr. Speziale discusses the commonalities of today’s market-beating growth stocks so that you can find the next ones in the future. WHAT YOU WILL LEARN IN THE BOOK: How you can turn $0 into $300,000 (and more) by saving, and then investing in growth stocksWhy growth investing is better than value investingWhat top growth stocks (“Capital Compounders”) have in common72 Rules for investing stocks; winning in the market, and managing a portfolioActual examples of tenbagger (10x return) and 100-bagger (100x return) stocks75+ events, and corporate developments that move stocksHow a hedge fund manager achieved a 24% compound annual return (since 1998!)50+ predictions for the futureExclusive interviews with a small-cap technology analyst, and a growth hedge fund managerHow to decode market psychology, and control your own behavioural biasesGrowth investing strategies from the world's top growth investorsDaily routine – how to stay on top of the stock market, and find new growth ideas100+ Free DIY investor resources (all of my favourites!)PLUS – FREE Investment Newsletter Subscription (inside the book) Capital Compounders is for both budding and seasoned investors. It’s entertaining (because finance can be dry), and includes lots of easy-to-learn tips and strategies on growth investing that you can apply in the stock market. Robin R. Speziale is a DIY Investor and Globe and Mail National Bestselling Author; Market Masters (2016). He's been investing in the stock market since 2005, and built a $300,000+ portfolio before 30. Mr. Speziale lives in Toronto, Ontario. Visit RobinRSpeziale.com and email Robin – [email protected].
Book Synopsis Big Data Beyond the Hype by : Zikopoulos
Download or read book Big Data Beyond the Hype written by Zikopoulos and published by McGraw-Hill/Osborne Media. This book was released on 2014-11-10 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data in a nutshell: It is the ability to retain, process, and understand data like never before. It can mean more data than what you are using today; but it can also mean different kinds of data, a venture into the unstructured world where most of today's data resides. In this book you will learn how cognitive computing systems, like IBM Watson, fit into the Big Data world. Learn about the concept of data-in-motion and InfoSphere Streams, the world's fastest and most flexible platform for streaming data. Capturing, storing, refining, transforming, governing, securing, and analyzing data are important topics also covered in this book.
Book Synopsis Introducing Data Science by : Davy Cielen
Download or read book Introducing Data Science written by Davy Cielen and published by Simon and Schuster. This book was released on 2016-05-02 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started. About the Book Introducing Data ScienceIntroducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You’ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You’ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. What’s Inside Handling large data Introduction to machine learning Using Python to work with data Writing data science algorithms About the Reader This book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. About the Authors Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors. Table of Contents Data science in a big data world The data science process Machine learning Handling large data on a single computer First steps in big data Join the NoSQL movement The rise of graph databases Text mining and text analytics Data visualization to the end user
Book Synopsis Developing High Quality Data Models by : Matthew West
Download or read book Developing High Quality Data Models written by Matthew West and published by Elsevier. This book was released on 2011-02-07 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models. The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool. This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling. - Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality - Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates - Develops ideas for creating consistent approaches to high quality data models
Book Synopsis Big Data Analytics with R and Hadoop by : Vignesh Prajapati
Download or read book Big Data Analytics with R and Hadoop written by Vignesh Prajapati and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.
Book Synopsis Hadoop Beginner's Guide by : Garry Turkington
Download or read book Hadoop Beginner's Guide written by Garry Turkington and published by Packt Publishing Ltd. This book was released on 2013-02-22 with total page 675 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is arriving faster than you can process it and the overall volumes keep growing at a rate that keeps you awake at night. Hadoop can help you tame the data beast. Effective use of Hadoop however requires a mixture of programming, design, and system administration skills. "Hadoop Beginner's Guide" removes the mystery from Hadoop, presenting Hadoop and related technologies with a focus on building working systems and getting the job done, using cloud services to do so when it makes sense. From basic concepts and initial setup through developing applications and keeping the system running as the data grows, the book gives the understanding needed to effectively use Hadoop to solve real world problems. Starting with the basics of installing and configuring Hadoop, the book explains how to develop applications, maintain the system, and how to use additional products to integrate with other systems. While learning different ways to develop applications to run on Hadoop the book also covers tools such as Hive, Sqoop, and Flume that show how Hadoop can be integrated with relational databases and log collection. In addition to examples on Hadoop clusters on Ubuntu uses of cloud services such as Amazon, EC2 and Elastic MapReduce are covered.
Book Synopsis Business Intelligence in Microsoft SharePoint 2013 by : Norm Warren
Download or read book Business Intelligence in Microsoft SharePoint 2013 written by Norm Warren and published by Pearson Education. This book was released on 2013-05-15 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the business intelligence features in SharePoint 2013—and use the right combination of tools to deliver compelling solutions. Take control of business intelligence (BI) with the tools offered by SharePoint 2013 and Microsoft SQL Server 2012. Led by a group of BI and SharePoint experts, you’ll get step-by-step instructions for understanding how to use these technologies best in specific BI scenarios—whether you’re a SharePoint administrator, SQL Server developer, or business analyst. Discover how to: Manage the entire BI lifecycle, from determining key performance indicators to building dashboards Use web-based Microsoft Excel services and publish workbooks on a SharePoint Server Mash up data from multiple sources and create Data Analysis Expressions (DAX) using PowerPivot Create data-driven diagrams that provide interactive processes and context with Microsoft Visio Services Use dashboards, scorecards, reports, and key performance indicators to monitor and analyze your business Use SharePoint to view BI reports side by side, no matter which tools were used to produced them
Book Synopsis Analytics at Work by : Thomas H. Davenport
Download or read book Analytics at Work written by Thomas H. Davenport and published by Harvard Business Press. This book was released on 2010 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a follow-up to the successful Competing on Analytics, authors Tom Davenport, Jeanne Harris, and Robert Morison provide practical frameworks and tools for all companies that want to use analytics as a basis for more effective and more profitable decision making. Regardless of your company's strategy, and whether or not analytics are your company's primary source of competitive differentiation, this book is designed to help you assess your organization's analytical capabilities, provide the tools to build these capabilities, and put analytics to work. The book helps you answer these pressing questions: What assets do I need in place in my organization in order to use analytics to run my business? Once I have these assets, how do I deploy them to get the most from an analytic approach? How do I get an analytic initiative off the ground in the first place, and then how do I sustain analytics in my organization over time? Packed with tools, frameworks, and all new examples, Analytics at Work makes analytics understandable and accessible and teaches you how to make your company more analytical.
