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).
About this Course
Skills you will gain
University of Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
- 5 stars55.14%
- 4 stars25.19%
- 3 stars12.01%
- 2 stars4.32%
- 1 star3.32%
TOP REVIEWS FROM APPLIED TEXT MINING IN PYTHON
Course is great except for the auto grader issues. Please look into the issue. I would like to take this opportunity and thank Prof V. G. Vinod Vydiswaran and all those who helped me to complete it.
Excellent course! Video lectures are high quality, with realistic problems and applications. Exercises are reasonably challenging, and all quite fun to do! Strongly recommend this course
A little bit stretched my python skill, but learned a lot. Forum is a good place, and maybe next I will join some study group online or offline to have more discussions.
Passionate instructor and a great primer on how software can infer useful data from text. Gives a preliminary understanding on the algorithms used in scikit learn and nltk.
About the Applied Data Science with Python Specialization
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
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