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Learner Reviews & Feedback for Applied Text Mining in Python by University of Michigan
3,824 ratings
About the Course
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).
This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python.
Top reviews
BK
Jun 25, 2018
Would love to see these courses have more practice questions in each weeks lesson. Would be helpful for repetition sake, and learning vs only doing each question once in the assignments.
JL
Oct 25, 2017
The course itself is good, but the assigment system is not robust and some sentences are also ambiguous to users. Seeing from the forums, many users get confused in the assigments.
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