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.
提供方
您将学到的内容有
Apply basic natural language processing methods
Describe the nltk framework for manipulating text
Understand how text is handled in Python
Write code that groups documents by topic
您将获得的技能
教学大纲 - 您将从这门课程中学到什么
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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来自Applied Text Mining in Python的热门评论
Lectures are very good with a perfect explanation. More than lectures I liked the assignment questions. They are worth doing. You will get to know the basic foundation of text mining. :-)
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.
讲师
V. G. Vinod Vydiswaran
Assistant Professor关于 密歇根大学
关于 借助 Python 应用数据科学 专项课程
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