1. NTC 2014 : NLP/ML Track Danish Contractor

2. Suggestions This presentation provides links to data sets as well as tools and resources for working on Natural Language Processing and Machine Learning track. Govt website links are a good place to look for social data sets. We would recommend you browse through the data sets in this presentation and see if any of them interests you. We have also outlined a few examples to get ideas on how people are applying NLP/ML to real world problems Your creativity is to think of a problem you think could get solved by analyzing these data sets and applying NLP/ML techniques. We don't want you to be over ambitious. However, we want you to be as innovative and as effective as possible. Feel free to reach out to us in case of any queries.

3. Deliverable Now that you are interested in building NLP/ML, let us be clear on the deliverable from your side. You can either submit a standalone mobile application or a standalone web application or a combination of both. You should accompany your submission with clear set of instructions so that we can run your application at our end. To stress this point, we again note that we should be able to install and run your system at our end without any glitches. This means that you should test your application in different environments before you make the final submission. However, you can clearly specify under which environments you application works, for instances, Android 4.4, or Amazon cloud service etc. You application should work seamlessly with open source data set and open source packages, for instance, if your application is supposed to load data from a data source, the loading should happen automatically without any manual efforts. In next few slides, we equip you with open source tools and techniques you can use to build your applications.

4. NLP/ML Tools and packages http://nlp.stanford.edu/downloads/ http://www.cs.waikato.ac.nz/ml/weka/ http://mallet.cs.umass.edu/ http://svmlight.joachims.org/ http://lucene.apache.org/ http://dbpedia-spotlight.github.io/demo/# http://wordnet.princeton.edu/wordnet/download/ https://opennlp.apache.org/

5. NLP/ML Tools and Packages http://mogadala.com/Toolkits_and_Datase ts.htmlhttp://mogadala.com/Toolkits_and_Datase ts.html http://www.isical.ac.in/~fire/resources.html

6. NLP Tutorials Tutorials on the StanfordNLP page, Lucene Documentation, OpenNLP, Weka tutorials are a good place to start.