A Data Science Central Community
First of all, our team is absolutely delighted that Judea Pearl won the ACM Turing Award, widely considered the "Nobel Prize in Computing". For well over a decade we've been exclusively committed to developing software based on Bayesian networks, a paradigm established by Judea for reasoning under uncertainty. We are confident that this award will be a great accelerator in gaining broad acceptance for this paradigm, or rather, as we said half-jokingly to Judea in Nov. 2010, the "evangelization" of Bayesian networks.
The next training seminars "Bayesian Networks for Expert Knowledge Modeling and Data Mining" will take place in:
We cover all the fundamentals of Bayesian Networks and Data Mining, so no prior knowledge is required other than a basic familiarity with mathematical and statistical concepts. In conjunction with the seminar, participants have access to a 60-day unrestricted license of BayesiaLab Professional Edition, so they can experience the full array of features through the hands-on exercises.
Please join us at the following events:
Here is the list of our most recent White Papers available in the BayesiaLab resources section:
A free 30-day evaluation version of the latest release of BayesiaLab 5.0 Professional Edition is available for immediate download.
This will allow you to experiment with new the features of BayesiaLab 5.0, plus you can try out all the Bayesian network examples explained in our series of white papers.
Last year we created a discussion group on LinkedIn dedicated to Bayesian Belief Networks with BayesiaLab. Today, this group has almost 900 members and it hosts a wide range of interesting discussions and also features the latest announcements from Bayesia. You will also find Frequently Asked Questions (FAQ) in this group, with experts from BayesiaLab and users of the program exchanging the latest tips and tricks.
You can join our LinkedIn group by clicking here.
With best regards,
Dr. Lionel Jouffe
6, rue Leonard de Vinci
Tel.: +33(0)2 43 49 75 69
Fax: +33(0)2 43 49 75 83
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