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
- 5 stars54.96%
- 4 stars25.15%
- 3 stars12.05%
- 2 stars4.36%
- 1 star3.45%
TOP REVIEWS FROM APPLIED TEXT MINING IN PYTHON
La variedad de temas del curso lo hace un curso muy recomendable. El nivel de las tareas está de acuerdo a lo que se enseña. Muy recomendado como un primer acercamiento al tema.
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.
This course give the basic idea in each module existed in text and natural language processing kits. A lot more for self-explore, but this will intrigue to begin sooner and learn wider.
Course is well explained with practice exercise. Only suggestion is that for assignment there is no way to find why a particular output is wrong. There should be some hint for it.
About the Applied Data Science with Python Specialization
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