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Evaluation of Python Machine Learning APIS for Text Classification

by Jaganadh Gopinadhan (speaking)

Scientific Computing
Session type
Technical level


The proposed talk contains study on the capability of Python Machine Learning Libraries to deal with text classification. The talk evaluates classification algorithms implemented in NLTK and sklearn.


This talk presents an empirical evaluation of text classification capabilities of two popular Python Machine Learning libraraies NLTK and sklearn. The study compares performance of different classification algorithms implemented in both of the libraries. At the same time the talk investigates the capability of thse tools to deal with social media text for classification task too.

Talk outline

1) Introduction to text classification 2) Text Classification with skelarn 3) Text Classification with NLTK 4) Comparison of sklearn and NLTK 5) Dealing with social media text 6) Results and Discussions

Speaker bio

Jaganadh G is a Text Analytics / Mining Researcher and Developer. His areas of interest are Text Mining / Analytics, Natural Language Processing, Machine Learning, Sentiment Analysis, Big-Date, Hadoop and Allied Technologies, NoSQL and Free and Open Source Software. He holds post graduate degree in Sanskrit Nyaya (Indian Logic) from University of Kerala. His ramblings on technological trends and book reviews can be found at http://jaganadhg.in .