Panel On Data

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Making Policies for Children: A Study of the Federal Process

National Research Council; Division of Behavioral and Social Sciences and Education; Commission on Behavioral and Social Sciences and Education; Committee on Child Development Research and Public Policy; Panel for the Study of the Policy Formation Process, 1982

EPUB

Designing the 2010 Census: First Interim Report

National Research Council; Commission on Behavioral and Social Sciences and Education; Committee on National Statistics; Panel on Research on Future Census Methods; Benjamin F. King; Michael L. Cohen; Committee on National Statistics; National Academy of Sciences,, 2000

EPUB

Improving Measures of Science, Technology, and Innovation: Interim Report

National Research Council; Policy and Global Affairs; and Economic Affairs Technology Board on Science; Division of Behavioral and Social Sciences and Education; Committee on National Statistics; and Innovation Indicators for the Future Technology Panel on Developing Science; Kaye Husbands Fealing; Andrew W. Wyckoff; Robert E. Litan, 2012

EPUB

Measuring Food Insecurity and Hunger: Phase 1 Report

National Research Council; Division of Behavioral and Social Sciences and Education; Committee on National Statistics; Panel to Review U.S Department of Agriculture's Measurement of Food Insecurity and Hunger, 2005

EPUB

An Assessment of the National Institute of Standards and Technology Physics Laboratory: Fiscal Year 2008

National Research Council; Division on Engineering and Physical Sciences; Laboratory Assessments Board; Panel on Physics, 2008

EPUB

An Assessment of the National Institute of Standards and Technology Materials Science and Engineering Laboratory: Fiscal Year 2008

National Research Council; Division on Engineering and Physical Sciences; Laboratory Assessments Board; Panel on Materials Science and Engineering, 2008

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Panel. Revista de arte rupestre

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Data on the Web. From Relational to Semistructured Data and XML.: From Relations to Semistructured Data and XML

Serge Abiteboul, Peter Buneman, Dan Suciu, 1999

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Data on the Web: From Relations to Semistructured Data and XML (The Morgan Kaufmann Series in Data Management Systems)

Serge Abiteboul, Peter Buneman, Dan Suciu, 1999

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Mastering Entity Framework: Effortlessly produce data-driven applications for .NET to address the competing demands of data storage and data modeling with Entity Framework

Rahul Rajat Singh, 2015

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Data Preparation for Data Mining Using SAS (The Morgan Kaufmann Series in Data Management Systems)

Mamdouh Refaat, 2006

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Data Warehousing And Business Intelligence For e-Commerce (The Morgan Kaufmann Series in Data Management Systems) (The Morgan Kaufmann Series in Data Management Systems)

Alan R. Simon, Steven L. Shaffer, 2001

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Advances in Data Analysis: Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks

Ramón Alvarez-Esteban, Olga Valencia, Mónica Bécue-Bertaut (auth.), Christos H. Skiadas (eds.), 2010

PDF

Advances in Data Analysis: Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks

Ramón Alvarez-Esteban, Olga Valencia, Mónica Bécue-Bertaut (auth.), Christos H. Skiadas (eds.), 2010

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Big Data Analytics Using Splunk: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources

Peter Zadrozny, Raghu Kodali, 2013

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Big Data Analytics Using Splunk: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources

Peter Zadrozny, Raghu Kodali, 2013

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Big Data Analytics with R and Hadoop: Set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics

Vignesh Prajapati, 2013

PDF

Big data, open data and data development

نتایج جستجو

Making Policies for Children: A Study of the Federal Process

Designing the 2010 Census: First Interim Report

Improving Measures of Science, Technology, and Innovation: Interim Report

Measuring Food Insecurity and Hunger: Phase 1 Report

An Assessment of the National Institute of Standards and Technology Physics Laboratory: Fiscal Year 2008

An Assessment of the National Institute of Standards and Technology Materials Science and Engineering Laboratory: Fiscal Year 2008

Panel. Revista de arte rupestre

Data on the Web. From Relational to Semistructured Data and XML.: From Relations to Semistructured Data and XML

Data on the Web: From Relations to Semistructured Data and XML (The Morgan Kaufmann Series in Data Management Systems)

Mastering Entity Framework: Effortlessly produce data-driven applications for .NET to address the competing demands of data storage and data modeling with Entity Framework

Data Preparation for Data Mining Using SAS (The Morgan Kaufmann Series in Data Management Systems)

Data Warehousing And Business Intelligence For e-Commerce (The Morgan Kaufmann Series in Data Management Systems) (The Morgan Kaufmann Series in Data Management Systems)

Advances in Data Analysis: Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks

Advances in Data Analysis: Theory and Applications to Reliability and Inference, Data Mining, Bioinformatics, Lifetime Data, and Neural Networks

Big Data Analytics Using Splunk: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources

Big Data Analytics Using Splunk: Deriving Operational Intelligence from Social Media, Machine Data, Existing Data Warehouses, and Other Real-Time Streaming Sources

Big Data Analytics with R and Hadoop: Set up an integrated infrastructure of R and Hadoop to turn your data analytics into Big Data analytics

Big data, open data and data development

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems)

Data Science for Business: What you need to know about data mining and data-analytic thinking

Data Science for Business: What you need to know about data mining and data-analytic thinking

Data Science for Business: What you need to know about data mining and data-analytic thinking

Data Science for Business: What you need to know about data mining and data-analytic thinking

Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)