Listing 1 - 10 of 75 | << page >> |
Sort by
|
Choose an application
Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes About This Book Implement Scala in your data analysis using features from Spark, Breeze, and Zeppelin Scale up your data anlytics infrastructure with practical recipes for Scala machine learning Recipes for every stage of the data analysis process, from reading and collecting data to distributed analytics Who This Book Is For This book shows data scientists and analysts how to leverage their existing knowledge of Scala for quality and scalable data analysis. What You Will Learn Familiarize and set up the Breeze and Spark libraries and use data structures Import data from a host of possible sources and create dataframes from CSV Clean, validate and transform data using Scala to pre-process numerical and string data Integrate quintessential machine learning algorithms using Scala stack Bundle and scale up Spark jobs by deploying them into a variety of cluster managers Run streaming and graph analytics in Spark to visualize data, enabling exploratory analysis In Detail This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you'll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX. Style and approach This book contains a rich set of recipes that covers the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala and Spark.
Choose an application
Data mining and data modeling are hot topics and are under fast development. Because of their wide applications and rich research contents, many practitioners and academics are attracted to work in these areas. With a view to promoting communication and collaboration among the practitioners and researchers in Hong Kong, a workshop on data mining and modeling was held in June 2002. Prof Ngaiming Mok, Director of the Institute of Mathematical Research, The University of Hong Kong, and Prof Tze Leung Lai (Stanford University), C V Starr Professor of the University of Hong Kong, initiated the work
Management Information System --- dataverwerking --- econometrie --- forecasting --- markov-processen --- regressie-analyse --- tijdreeksanalyse --- wiskundige statistiek --- Data mining --- Database searching. --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Electronic information resource searching
Choose an application
Computer algorithms. --- Querying (Computer science) --- Database searching. --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Electronic information resource searching --- Database interrogation --- Interrogation of databases --- Database searching --- Reporting (Computer science) --- WHOIS (Computer network protocol) --- Algorithms
Choose an application
In the Information Society, information holds the master key to economic influence. Similarity Search: The Metric Space Approach will focus on efficient ways to locate user-relevant information in collections of objects, the similarity of which is quantified using a pairwise distance measure. This book is a direct response to recent advances in computing, communications and storage which have led to the current flood of digital libraries, data warehouses and the limitless heterogeneity of internet resources. Similarity Search: The Metric Space Approach will introduce state-of-the-art in developing index structures for searching complex data modeled as instances of a metric space. This book consists of two parts. Part 1 presents the metric search approach in a nutshell by defining the problem, describes major theoretical principals, and provides an extensive survey of specific techniques for a large range of applications. Part 2 concentrates on approaches particularly designed for searching in very large collections of data. Similarity Search: The Metric Space Approach is designed for a professional audience, composed of academic researchers as well as practitioners in industry. This book is also suitable as introductory material for graduate-level students in computer science.
Database searching. --- Data structures (Computer science) --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Electronic information resource searching
Choose an application
Computer. Automation --- Geographic information systems. --- Database searching. --- Systèmes d'information géographique --- Bases de données --- Interrogation --- Systèmes d'information géographique --- Bases de données --- Database searching --- Geographic information systems --- Geographical information systems --- GIS (Information systems) --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Information storage and retrieval systems --- Electronic information resource searching --- Geography
Choose an application
Information retrieval --- Database searching --- Information storage and retrieval systems --- Online bibliographic searching --- Reference services (Libraries) --- -Reference services (Libraries) --- -Libraries --- Library reference services --- Reference work (Libraries) --- Information services --- Public services (Libraries) --- On-line bibliographic searching --- Electronic information resource searching --- Searching, Bibliographical --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Management. --- Automation --- -Management --- Reference department --- -Management. --- Libraries --- Management --- Automation&delete&
Choose an application
The theory of R-trees is a well-established and important area of geometric group theory and in this book the authors introduce a construction that provides a new perspective on group actions on R-trees. They construct a group RF(G), equipped with an action on an R-tree, whose elements are certain functions from a compact real interval to the group G. They also study the structure of RF(G), including a detailed description of centralizers of elements and an investigation of its subgroups and quotients. Any group acting freely on an R-tree embeds in RF(G) for some choice of G. Much remains to be done to understand RF(G), and the extensive list of open problems included in an appendix could potentially lead to new methods for investigating group actions on R-trees, particularly free actions. This book will interest all geometric group theorists and model theorists whose research involves R-trees.
Geometric group theory. --- Trees (Graph theory) --- Trees (Graph theory). --- Database searching. --- Computer algorithms. --- Data structures (Computer science) --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Algorithms --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Electronic information resource searching --- Graph theory --- Group theory
Choose an application
In plain, uncomplicated language, and using detailed examples to explain the key concepts, models, and algorithms in vertical search ranking, Relevance Ranking for Vertical Search Engines teaches readers how to manipulate ranking algorithms to achieve better results in real-world applications. This reference book for professionals covers concepts and theories from the fundamental to the advanced, such as relevance, query intention, location-based relevance ranking, and cross-property ranking. It covers the most recent developments in vertical search ranking applications, such
Text processing (Computer science) --- Sorting (Electronic computers) --- Relevance --- Database searching --- Search engines --- Engineering & Applied Sciences --- Computer Science --- Programming --- Relevance. --- Database searching. --- Programming. --- Computer programming --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Electronic information resource searching --- Pertinence --- Relevancy --- Meaning (Philosophy) --- Meaning (Psychology) --- Computer sorting --- Electronic data processing --- Processing, Text (Computer science) --- Database management --- Information storage and retrieval systems --- Word processing
Choose an application
Enormous expanses of the Internet are unreachable with standard web search engines. This book provides the key to finding these hidden resources by identifying how to uncover and use invisible web resources. Mapping the invisible Web, when and how to use it, assessing the validity of the information, and the future of Web searching are topics covered in detail. Only 16 percent of Net-based information can be located using a general search engine. The other 84 percent is what is referred to as the invisible Web?made up of information stored in databases. Unlike pages on the visible Web, in
Online databases --- Database searching. --- Internet searching. --- Searching the Internet --- Web searching --- World Wide Web searching --- Electronic information resource searching --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- On-line databases --- Online data bases --- Databases --- Online information services
Choose an application
As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more. Algorithmic methods at the heart of successful data mining including tried and true techniques as well as leading edge methods. Performance improvement techniques that work by transforming the input or output. Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization in a new, interactive interface.
Data mining. --- Database searching. --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Electronic information resource searching --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching
Listing 1 - 10 of 75 | << page >> |
Sort by
|