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.
Created by: University of Michigan
Taught by: V. G. Vinod Vydiswaran, Assistant Professor
The course is six modules long and is designed to be completed in six weeks.
Module 1:
Working with Text in Python
Module 2:
Basic Natural Language Processing
Module 3:
Classification of Text
Module 4:
Topic Modeling
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