Re: [R] Free Webinar: Vendor Neutral Intro to Data Mining for AbsoluteBeginners, May 23, 2007

From: Brian Koch <bkoch_at_decisiondevelopment.com>
Date: Wed, 02 May 2007 14:39:09 -0500


Lisa: Can we expect to see R used [exclusively, I would hope] during your demonstration? Learning "how data mining models work: the inputs, the outputs, and the nature of the predictive mechanism" only makes sense for me if I can follow/retrace your steps on my systems. Thank you.

Brian J. Koch
Data Manager
Decision Development Inc

-----Original Message-----
From: r-help-bounces_at_stat.math.ethz.ch
[mailto:r-help-bounces_at_stat.math.ethz.ch] On Behalf Of Lisa Solomon Sent: Tuesday, May 01, 2007 1:46 PM
To: r-help
Subject: [R] Free Webinar: Vendor Neutral Intro to Data Mining for AbsoluteBeginners, May 23, 2007

ONLINE VENDOR NEUTRAL INTRO TO DATA MINING FOR ABSOLUTE BEGINNERS (no charge)

A non-technical data mining introduction for absolute beginners May 23, 2007, 10AM - 11AM PST Future Sessions (June 14, Sept 7)

To register for the webinar


  1. Go to https://salford.webex.com/salford/onstage/g.php?d=928318845&t=a
  2. Click "Enroll".
  3. On the registration form, enter your information and then click "Submit".

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!

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.

In one hour, we will discuss:

**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

**What kinds of questions can we answer with data mining

**How data mining models work: the inputs, the outputs, and the nature
of the predictive mechanism

**Evaluation criteria: how predictive models can be assessed and their
value measured

**Specific background knowledge to prepare you to begin a data mining
project.

Please do not hesitate to contact me if you have any questions.

Sincerely,
Lisa Solomon
lisas_at_salford-systems.com



R-help_at_stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.

R-help_at_stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Wed 02 May 2007 - 19:49:32 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Wed 02 May 2007 - 20:33:20 GMT.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.