MLTA 2013 - International Winter School on Machine Learning and Text Analytics

The primary aim of the Winter School on Machine Learning and Text Analytics is to train teachers/ professionals and Ph.D. students in the theoretical and practical aspects of Machine Learning and Text Analytics. The school will include keynotes, tutorials and laboratory sessions on relevant topics in the area. The school will also include tutorials and laboratory training in using the R software for problems in text analytics and natural language processing.
The school will be ideal for those who are working (or planning to start) in the areas of Machine Learning, Text Analytics, Natural Language Processing, Data Mining, Web Mining, Social Media Analytics etc. A one day pre-school tutorial to introduce the basics related to the area is scheduled on Dec. 15, 2013. It will have one session each on (a). Linear Algebra for Machine Learning, (b). Probability and Statistics for Machine Learning, (c). Information Theory for Machine Learning, and (d) Text Processing Basics.
The school will cover a wide range of topics in Machine Learning and Text Analytics. Some of the topics covered include: Statistical and Logical Learning, Bayesian Inference, Graphical Models, Reinforcement Learning, Support Vector Machines, Machine Learning and NLP, Computational Linguistics, Machine Translation, Text Classification and Clustering, Topic Modeling, Information Extraction, Named Entity Recognition, Document Summarization, Sentiment Analysis and Recommender Systems. The school will run largely in tutorial mode. Talks/ tutorials will be followed by Lab sessions to provide practical training to the participants on designing algorithmic formulations and programs for different tasks. The school includes about 8 hours of training in R during the initial few days, to meet this objective.