Data Sources Visual

Semantic Keyword-based Search on Structured Data Sources  eBooks & eLearning

Posted by roxul at May 8, 2016
Semantic Keyword-based Search on Structured Data Sources

Jorge Cardoso and Francesco Guerra, "Semantic Keyword-based Search on Structured Data Sources"
English | ISBN: 3319279319 | 2016 | 224 pages | PDF | 13 MB
Технологии анализа данных. Data Mining, Visual Mining, Text Mining, OLAP (Repost)

Технологии анализа данных. Data Mining, Visual Mining, Text Mining, OLAP - Иван Холод
2007 | ISBN: 5941579918 | DJVU | 2-е издание | 384 pages | 6.4 Mb

Книга является вторым, обновленным и дополненным, изданием учебного пособия в котором излагаются основные направления в области разработки корпоративных систем: организация хранилищ данных, распределенный, оперативный (OLAP), интеллектуальный (Data Mining), визуальный (Visual Mining) и текстовый (Text Mining) анализ данных.
Administrative Data Sources for Compiling Millennium Development Goals and Related Indicators

Administrative Data Sources for Compiling Millennium Development Goals and Related Indicators
ADB | 2011 | ISBN: 9789290921646 9789290922599 | 246 pages | PDF | 5 MB

The handbook serves as a reference tool for data producers on improving administrative data sources for compiling the Millennium Development Goals and other indicators.
Технологии анализа данных. Data Mining, Visual Mining, Text Mining, OLAP

Технологии анализа данных. Data Mining, Visual Mining, Text Mining, OLAP
DJVU + CD | 384 Стр. | ISBN: 5941579918 | Издатель: БХВ-Петербург | Серия: Учебное пособие | 2007 | 6 Mb + 78 Mb

Книга является вторым, обновленным и дополненным, изданием учебного пособия «Методы и модели анализа данных. OLAP и Data Mining». Излагаются основные направления в области разработки корпоративных систем: организация хранилищ данных, распределенный, оперативный (OLAP), интеллектуальный (Data Mining), визуальный (Visual Mining) и текстовый (Text Mining) анализ данных. Приведено описание методов и алгоритмов решения основных задач анализа: классификации, кластеризации и др. Описание идеи каждого метода дополняется конкретным примером его применения.
Прилагается компакт-диск, содержащий стандарты Data Mining, библиотеку алгоритмов Xelopes, лабораторный практикум по интеллектуальному анализу данных и соответствующее программное обеспечение.
Introduction to Applied Demography: Data Sources and Estimation Techniques

Norfleet W. Rives, William J. Serow,"Introduction to Applied Demography: Data Sources and Estimation Techniques"
Sage Publications | 1984-07-01 ISBN: 0803921349 | 95 pages | PDF | 1 mb

Shifting demographic conditions constitute a potent force in contemporary society. Business and government agencies have responded to this force through an increasing use of demographic techniques and the consequent emergence of the field of applied demography.

Introduction to Data Analytics with KNIME  eBooks & eLearning

Posted by FenixN at Nov. 21, 2016
Introduction to Data Analytics with KNIME

Introduction to Data Analytics with KNIME
HDRips | MP4/AVC, ~562 kb/s | 1280x720 | Duration: 03:01:32 | English: AAC, 128 kb/s (2 ch) | 892 MB
Genre: Data Analytics

This is a hands-on basic course about data analytics and KNIME, and is designed for learners with little experience in data analytics or in programming. Taught by 24 year data analytics veteran Dr. Rosaria Silipo, it covers everything a beginning data analyst needs to know. You'll learn about importing data from common data sources and how to investigate data using visual exploration, ETL, data blending, and some machine learning algorithms.

Data Integration: The Relational Logic Approach (Repost)  eBooks & eLearning

Posted by leonardo78 at Nov. 1, 2016
Data Integration: The Relational Logic Approach (Repost)

Data Integration: The Relational Logic Approach by Michael Genesereth
Publisher: Morgan and Claypool | 2010 | ISBN: 1598297414 | 110 pages | PDF | 0,8 MB

Data integration is a critical problem in our increasingly interconnected but inevitably heterogeneous world. There are numerous data sources available in organizational databases and on public information systems like the World Wide Web.

Pluralsight - Windows Store Apps - Data Binding in Depth [repost]  eBooks & eLearning

Posted by house23 at Aug. 28, 2016
Pluralsight - Windows Store Apps - Data Binding in Depth [repost]

Pluralsight - Windows Store Apps - Data Binding in Depth
MP4 | AVC 339kbps | English | 1024x768 | 15fps | 4h 33mins | AAC stereo 105kbps | 761 MB
Genre: Video Training

Every App displays some kind of data. When developing Windows Store Apps, you can use WinRT's Data Binding to bind the User Interface of your App to that data. With Data Bindings, there's no need to create Event Handlers to synchronize the data between different Controls in your UI, instead the Data Binding will do that job for you. The Data Binding-infrastructure of XAML-based frameworks is the base for the famous Model-View-ViewModel pattern (MVVM). This course teaches you how to use Data Bindings with all the tips and tricks you need to know. You'll learn how to create Data Bindings in XAML and C#, how to debug Data Bindings, how to use different data sources for a Data Binding like Dependency Properties, .NET Properties, Resources, relative Sources, and Collections.

Active Mining - New Directions of Data Mining (repost)  

Posted by MoneyRich at Oct. 11, 2015
Active Mining - New Directions of Data Mining (repost)

Active Mining - New Directions of Data Mining by Hiroshi Motoda
English | 29 July 2002 | ISBN: 158603264X | 304 Pages | PDF | 8 MB

The need for collecting relevant data sources, mining useful knowledge from different forms of data sources and promptly reacting to situation change is ever increasing. Active mining is a collection of activities each solving a part of this need, but collectively achieving the mining objective through the spiral effect of these interleaving three steps.
Pluralsight - Streams, Collectors, and Optionals for Data Processing in Java 8

Pluralsight - Streams, Collectors, and Optionals for Data Processing in Java 8
Size: 897MB | Duration: 4h 29m | Video: AVC (.mp4) 1024x576 15fps | Audio: AAC 44.1KHz 2ch
Genre: eLearning | Level: Advanced | Language: English

This course shows advanced patterns to process data in Java 8 using lambdas, streams, spliterators, optionals, and collectors. It shows how to build your own spliterators to connect streams to non-standard data sources, and to build your own collectors.