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).
Applied Text Mining in Python
This course is part of Applied Data Science with Python Specialization
Instructor: V. G. Vinod Vydiswaran
149,319 already enrolled
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What you'll learn
Understand how text is handled in Python
Apply basic natural language processing methods
Write code that groups documents by topic
Describe the nltk framework for manipulating text
Skills you'll gain
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There are 4 modules in this course
What's included
5 videos4 readings2 assignments1 programming assignment1 discussion prompt2 ungraded labs
What's included
4 videos2 assignments1 programming assignment1 discussion prompt1 ungraded lab
What's included
7 videos1 assignment1 programming assignment1 ungraded lab
What's included
4 videos4 readings2 assignments1 programming assignment
Instructor
Offered by
Recommended if you're interested in Data Analysis
University of Illinois Urbana-Champaign
University of Michigan
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Taking this course by University of Michigan may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
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