Advanced approximate sentence matching in Python

In our last post, we went over a range of options to perform approximate sentence matching in Python, an import task for many natural language processing and machine learning tasks.  To begin, we defined terms like: tokens: a word, number, or other "discrete" unit of text. stems: words that have had their "inflected" pieces removed based on

Revisiting text processing with R and Python

  Back in 2011, I covered the relative performance difference of the most popular libraries for text processing in R and Python.   In case you can't guess the answer, Python and NLTK  won by a significant margin over R and tm.  Text processing with R seemed simple on paper, but performance and flexibility limitations have

By |2013-05-25T21:19:25-04:00May 25th, 2013|Consulting, Programming|0 Comments

Natural Language Processing and Machine Learning for e-Discovery – Slides from guest lecture at MSU College of Law

  Fellow Computational Legal Studies blogger and MSU law prof Dan Katz invited me to give an expert guest lecture for his e-Discovery seminar.  This seminar, taught jointly with  Professor Candeub, is an excellent example of MSU's strategic pivot to deliver practical, 21st-century skills to their students.  The goal of the talk was to provide

By |2012-10-31T09:37:55-04:00October 31st, 2012|Consulting, Law, Technology|0 Comments

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