Text Mining in Data Science: An In-Depth Exploration Using NLTK

#textmining #datascience #signalprocessing #WIE #6G
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Text mining plays a crucial role in data science by transforming unstructured textual data into
meaningful insights. This exploration delves into the methodologies and applications of text mining using the
Natural Language Toolkit (NLTK), a powerful Python library for natural language processing. The talk will
highlight key techniques such as tokenization, stemming, lemmatization, part-of-speech tagging, and sentiment
analysis. By leveraging NLTK’s tools, data scientists can efficiently preprocess, analyze, and derive value from
text data across various domains, making it an essential component in the broader landscape of data-driven
decision-making.



  Date and Time

  Location

  Hosts

  Registration



  • Date: 22 Apr 2025
  • Time: 04:00 PM UTC to 06:00 PM UTC
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  • 1125 Colonel Dr
  • Ottawa, Ontario
  • Canada
  • Building: ME
  • Room Number: 4359

  • Contact Event Hosts
  • Starts 16 April 2025 02:00 AM UTC
  • Ends 22 April 2025 04:00 PM UTC
  • 7 in-person spaces left!
  • No Admission Charge


  Speakers

Topic:

Surbhi B. Khan

Biography:

Surbhi B. Khan is working in the School of Science, Engineering and Environment, Data Science Department at
the University of Salford, United Kingdom. She is Project Management Professional Certified from PMP, USA.
She is ranked among the top 2% of scientists globally for the second year in a row (2023 and 2024), as
acknowledged by Stanford University and Elsevier. She is supervising/co-supervising a number of PhDs and
research associates. She has published over 200 articles and books in high indexed outlets with her students
and colleagues. She has been awarded with best paper awards, and several other recognitions. She is also
serving as Deputy EIC in TCE letters, Associate editor in IEEE Transactions on Consumer Electronics, HCIS and
EAAI journals and Guest editor in many other reputed journals. She is working on some projects in external
funding from UK, India, and MiddleEastern Institutes.
She has been serving as session chairs in many IEEE conferences, been invited as a resource person at
International Conferences and FDP's and has enjoys honorary positions by advising universities to achieve
research and teaching excellence. She is also a member in the Women in Data Science Ambassador 2024. Her
research interests are Machine Learning/Deep learning, Data Science in Healthcare, Text Recognition and
Detection.

Address:United Kingdom