Learn how text mining techniques in data science work

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Data Science Webinars

Learn how text mining techniques in data science work

August 7, 2019|Smitha Ganesh

Smitha is an experienced data scientist, with 14+ years of industry experience and a proven track record of leading, designing and developing solutions to enable businesses in the aviation, oil & gas and automotive domains achieve their $MM productivity. Currently a Principal Consultant at ThoughtWorks, India, she is working on projects that help clients become AI mature. She has a master’s degree in structural engineering and has earlier worked with GM and GE on simulations and machine learning techniques. She has strong interests in applied machine learning, like pattern recognition, text mining, trend analysis and anomaly detection. Also, Smitha is working with a few universities in helping them align their curriculum to current data science trends.

Key takeaways for you

  • What is text mining
  • Is text mining part of machine learning
  • What is document sanitisation and why is it so critical
  • Use cases of document sanitisation
  • Sensitive information identification vs removal strategy
  • Techniques to identify sensitive information – Named entity recognition (NER) and sentence similarity
  • Final look of sanitised document

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