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Applied Text Mining in Python
University of Michigan
V. G. Vinod Vydiswaran
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Free? Partially: Some Free Content, Some Paid
$0.00 - $73.00
Tags: nltk / supervised learning / text classification / text manipulation / text mining / topic modelling
This course is #4 of 5 in the Applied Data Science with Python Specialization from the University of Michigan.
“This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).”
Recommended Prerequisites: "Intended for learners who have basic python or programming background…Minimal statistics background" expected.
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