Archive for September 2007

IBM Joins Community

September 14, 2007

10 September 2007 — The community today announced that IBM will be joining the community to collaborate on the development of software. IBM will be making initial code contributions that it has been developing as part of its Lotus Notes product, including accessibility enhancements, and will be making ongoing contributions to the feature richness and code quality of Besides working with the community on the free productivity suite’s software, IBM will also leverage technology in its products.

read the full press release at


Machine Learning Development with Perl

September 11, 2007

I just posted in PerlMonks a draft of a 45 minutes-long talk on Machine Learning Development with Perl. Here is an extract of that post:


Machine Learning Development with Perl

The development of machine learning applications can be seen as a three-phase process involving: preparation, modeling, and implementation (See Fig. 1).

As a developer, you have to move back and forth between phases until you get a satisfactory result.


In the preparation phase, you work with your customer to define the problem. You proceed, then, to gather some data. After that, you analyze the data and do some cleaning if necessary and select the features you are going to use in the model. Based on the type of problem, you may decide what type of model you want to develop: a classifier, an estimator, or a clustering application.


In the modeling phase, you do the model selection in case you did not do it in the preparation phase and then you do the development and finally you do the evaluation. Based on the results you get, you may decide to got back to the preparation phase and select other features, other cleaning method, or maybe other type of model.


In the implementation phase, you simply implement your model. One important consideration is that your model should continue learning from new data. Sometimes, in machine learning, your model works well initially but when the data grow significantly then the model does not perform as well as before. This is why it is important to allow the model to continue learning as more data become available.


The full post ( including source code ) is available at RFC: Machine Learning Development with Perl



Presenting AranduCorp

September 10, 2007

AranduCorp is a consulting firm focused on helping organizations improve their business processes, marketing, and sales. AranduCorp offers training and consulting services on predictive analytics and will soon offer affordable predictive analytics software solutions for small and medium size businesses.

For more information visit:

AranduCorp’s Website

AranduCorp’s Blog