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Η παρουσίαση στα Αγγλικά.
Η παρουσίαση στα Αγγλικά.

... 2. Use URIs so that people can look up (dereference) those names. 3. When someone looks up a URI, provide useful information. 4. Include links to other URIs so that they can discover more things. ...
Holland, Matthew / Hoggarth, Andrew: “Hydrographic Data Models
Holland, Matthew / Hoggarth, Andrew: “Hydrographic Data Models

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How to Make the Data Elephant Dance?

... Data modeling and analysis: charts, or graphs that describe what has given negative feedback with 2/13 and Data modeling and analysis is a forwardhappened so far on the basis of 13-2-13 as the dates on which they looking step that recognizes patterns thousands of customer responses ordered pizza. If ...
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P values are only an index to evidence: 20th- vs. 21st

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Statistical Learning Methods

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MULTI-LAYERED FRAMEWORK FOR DISTRIBUTED DATA MINING

... capabilities. The system provides high level of asynchronous background operations, performing most data intensive operations in the background or offline and allowing users to continue their work. The system minimizes the flow of data across the network. ...
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Sample IEEE Paper for A4 Page Size (use style: paper title)

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The Data Growth Problem

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Week 6 - Ken Cosh

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Data Analysis for Competition Policy: an Introduction to Econometrics

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Forecasting

Forecasting is the process of making predictions of the future based on past and present data and analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term. Both might refer to formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgmental methods. Usage can differ between areas of application: for example, in hydrology, the terms ""forecast"" and ""forecasting"" are sometimes reserved for estimates of values at certain specific future times, while the term ""prediction"" is used for more general estimates, such as the number of times floods will occur over a long period.Risk and uncertainty are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts. In any case, the data must be up to date in order for the forecast to be as accurate as possible.
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