Applied Text Mining in Python Coursera

Overview

The Applied Text Mining in Python course offered by Coursera in partnership with University of Michigan 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.

Key facts

• 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.

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'll gain

• Python Programming

• Machine Learning

• Data Analysis

• Applied Machine Learning

• Machine Learning Algorithms

• Algorithms

• Human Learning