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).
Este curso forma parte de Programa especializado: Ciencias de los Datos Aplicada con Python
Acerca de este Curso
Qué aprenderás
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
Habilidades que obtendrás
- Natural Language Toolkit (NLTK)
- Text Mining
- Python Programming
- Natural Language Processing
Ofrecido por
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Programa - Qué aprenderás en este curso
Module 1: Working with Text in Python
Module 2: Basic Natural Language Processing
Module 3: Classification of Text
Module 4: Topic Modeling
Reseñas
- 5 stars54,98 %
- 4 stars25,13 %
- 3 stars12,05 %
- 2 stars4,36 %
- 1 star3,45 %
Principales reseñas sobre APPLIED TEXT MINING IN PYTHON
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. :-)
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.
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.
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.
Acerca de Programa especializado: Ciencias de los Datos Aplicada con Python

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