Machine learning in web application? There are a lot of outstanding machine learning/data mining standalone applications available in different languages like Java, Python, and others.
However, I wonder, practically, in case of applying machine learning techniques into a web environment, is there anything existing that can be handy to use? E.g. any framework or library to apply machine learning in web applications?
I understand things can be different in different language environment, but if you can refer to any kind of related information, it could be helpful. Thanks!
 A: RapidMiner is a framework implemented in Java that integrates with Weka and R. The only caveat to be mindful of here is integration into web services is a premium service and not in the community version of the system.
As for something you could throw together and run directly in a browser without plugins or premium services there is Brain which can do Neural Betworks, Naive Bayes, and Cross Validation. There are numerous other implementations for the web (e.g. javascript of K-means, Neural Networks, Genetic Algorithms, etc.) most of these though are for generally smaller sets of algorithms instead of larger collections you tend to find in R packages or in systems like Mahout and Weka. So you might end up having to have to piece a complete library yourself depending on what you're looking for.
Since your question is fairly generic its hard to provide more details, but that should be an adequate starting point. If you have a more detailed question feel free to ask, I hope this helps.
A: rApache embeds R inside the Apache web server. It works very well, although I prefer Python for larger projects. To get first insight into rApache visit the Jeroen's homepage. 
