From the description of the seminar:
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.
Data mining and the related field of machine learning deal with finding patterns in large sets of data. This is very useful for trying to understand and model complex natural phenomena, and bioinformaticians have not been shy to take advantage of these methods. Just look at any recent issue of BMC Bioinformatics or PLoS Computational Biology and you will see a number of articles involving SVMs, Neural Networks, and Bayesian networks.
This webinar is geared towards people with little or no understanding of data mining, so it should be a good introduction if you haven’t learned about machine learning or data mining. If you are interested in learning more, there are some good tutorials online at here, and here. Videolectures.net and Peteris’s blog include a number of video lectures on the machine learning.
To sign up, go to the event description and click “enroll.”