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 is part of the Applied Data Science with Python Specialization
About this Course
What you will 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 will gain
- Natural Language Toolkit (NLTK)
- Text Mining
- Python Programming
- Natural Language Processing
Start working towards your Master's degree
Syllabus - What you will learn from this course
Module 1: Working with Text in Python
Module 2: Basic Natural Language Processing
Module 3: Classification of Text
Module 4: Topic Modeling
- 5 stars54.98%
- 4 stars25.10%
- 3 stars12.05%
- 2 stars4.41%
- 1 star3.44%
TOP REVIEWS FROM APPLIED TEXT MINING IN PYTHON
Excellent course to get started with text mining and NLP with Python. The course goes over the most essential elements involved with dealing with free text. Definitely worth the time I spent on it.
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.
Everything was awesome, assignment 2 was my favorite in a long while in this specialization series. Week 4 was a little weak, and felt rushed. Overall, I enjoyed this course 4 of the 5.
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
About the Applied Data Science with Python Specialization
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