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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html lang="en" dir="ltr">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
<title>The International Biometric Society Australasian Region - Conferences</title>
<link href="conf.css" type="text/css" rel="stylesheet">
<script type="text/javascript">
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
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<script type="text/javascript">
var pageTracker = _gat._getTracker("UA-3244064-2");
pageTracker._initData();
pageTracker._trackPageview();
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<body>
<table class="maintable">
<tr class="banner">
<td colspan="2" class="banner"><table class="topbox" border=0>
<tr>
<td class="title">
<center> The International Biometric Society<BR> Australasian Region</center>
</td>
<td rowspan="2" style="border-color: #583af2; border-style: groove;
border-width: thin;">
<a href="http://www.tibs.org/">
<img src="ibslogo.jpg" alt="[ibslogo]" width="120" height="120" style="vertical-align: middle;" /></a>
</td>
</tr>
<tr>
<td class="dates">
<p>3 July 2007 Hobart, TAS<span style="color: #b1e8ff;"></span></p>
</td>
</tr>
</table></td>
</tr>
<tr>
<td valign="top" class="left-outer" width=0>
<table class="left-inner">
<tr>
<td class="l-i">
<table class="sidemenu">
<tr>
<td><a href=".">Home</a></td>
</tr>
<tr>
<td><a href="about.html">About us</a></td>
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<tr>
<td><a href="council.html">Regional council</a></td>
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<tr>
<td><a href="news.html">News</a></td>
</tr>
<tr>
<td><a href="prizes.html">Prizes / Awards</a></td>
</tr>
<tr>
<td> Conferences<br>
<table width="157">
<tr>
<td><a href="http://www.biometrics.org.au/conf/">Biometrics 2007</a></td>
</tr>
<!--<tr><td><a href="./bca.html">BCA Workshop 2007</a></td></tr>-->
<!--<tr><td><a href="./salford.html">Data Mining Introduction</a></td></tr>-->
<tr>
<td><a href="http://www.conferencepartners.ie/ibcdublin2008/">IBC 2008</a></td>
</tr>
<tr>
<td><a href="http://www.stat.mq.edu.au/conf/ASM">Advanced Statistical Models</a></td>
</tr>
<tr>
<td><a href="http://www.thegeorgeinstitute.org/events/calendar-of-events-details-/event-details-administration.cfm?obj_uuid=45FE2D95-F608-663C-FEEC-E143EA693E45">Cluster Randomised Trials</a></td>
</tr>
</table></td>
</tr>
<tr>
<td><a href="memberservices.html">How to join</a></td>
</tr>
<tr>
<td><a href="links.html">Useful links</a></td>
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<td><a href="contacts.html">Contact Us</a></td>
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</table>
</td>
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</table>
</td>
<td valign="top" class="bodytext">
<!-- ======== BEGIN PAGE TEXT =================== -->
<div class="pagename">
<h1>ONLINE VENDOR NEUTRAL INTRO TO DATA MINING FOR ABSOLUTE BEGINNERS</h1>
</div>
<div class="text"><h2>A non-technical data mining introduction for absolute beginners</h2>
<p> </p>
July 3, 2007, 9AM: Australian Eastern Standard Time<br>
Future Sessions in other timezones: (July 24, August 9, September 7)<br>
<br>
To register for the webinar <br>
------------------------------------------------------- <br>
1. Go to <a href="https://salford.webex.com/salford/onstage/g.php?t=a&d=926728704">https://salford.webex.com/salford/onstage/g.php?t=a&d=926728704</a><br>
2. Click "Enroll". <br>
3. On the registration form, enter your information and then click "Submit".<br>
<br>
Once you have registered, you will receive a confirmation email message with instructions on how to join the event, as well as audio and system requirements. Please read this confirmation email carefully!<br>
<br>
This one-hour webinar is a perfect place to start if you are new to data mining and have little-to-no background in statistics or machine learning. <br>
<br>
In one hour, the following will be discussed:<ul><li>Data basics: what kind of data is required for data mining and predictive analytics; In what format must the data be; what steps are necessary to prepare data appropriately </li>
<li>What kinds of questions can we answer with data mining</li>
<li>How data mining models work: the inputs, the outputs, and the nature of the predictive mechanism </li>
<li>Evaluation criteria: how predictive models can be assessed and their value measured </li>
<li>Specific background knowledge to prepare you to begin a data mining project.<br>
<br>
</li>
</ul>
</div>
<!-- ======== END PAGE TEXT ===================== --> </td>
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<td colspan="2" class="foot">
<p class="lastupdated"> Last updated 29 December 2006.</p></td>
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</body>
</html>