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).
Ce cours fait partie de la Spécialisation Science des données appliquée avec Python
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À propos de ce cours
Ce que vous allez apprendre
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
Compétences que vous acquerrez
- Natural Language Toolkit (NLTK)
- Text Mining
- Python Programming
- Natural Language Processing
Offert par

Université du 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.
Programme de cours : ce que vous apprendrez dans ce cours
Module 1: Working with Text in Python
Module 2: Basic Natural Language Processing
Module 3: Classification of Text
Module 4: Topic Modeling
Avis
- 5 stars55,08 %
- 4 stars25,25 %
- 3 stars12 %
- 2 stars4,34 %
- 1 star3,30 %
Meilleurs avis pour APPLIED TEXT MINING IN PYTHON
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.
Love the focus on conceptual text processing and practical guides to implementation in python, but the assignment grader was extremely specific for no reason, especially the Week3 assignment.
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.
À propos du Spécialisation Science des données appliquée avec Python
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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