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Applied Text Mining in Python
  • Level Professional
  • المدة 25 ساعات hours
  • الطبع بواسطة University of Michigan
  • Offered by

عن

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 should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python.

الوحدات

Module 1: Working with Text in Python

    • 5 Videos
    • 4 Readings
    • 1 Discussion
    • 2 Lab
    • 1 Assignment
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1 Assignment

  • Practice Quiz

1 Discussions

  • Introduce Yourself

2 Labs

  • Working with Text
  • Regex with Pandas and Named Groups

5 Videos

  • Introduction to Text Mining
  • Handling Text in Python
  • Regular Expressions
  • Demonstration: Regex with Pandas and Named Groups
  • Internationalization and Issues with Non-ASCII Characters

4 Readings

  • Syllabus
  • Help us learn more about you!!
  • Notice for Auditing Learners: Assignment Submission
  • Resources: Common issues with free text

Week 1 - Assignments

    • 1 Programming
    • 1 Assignment
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1 Programming

  • Assignment 1

1 Assignment

  • Module 1 Quiz

Module 2: Basic Natural Language Processing

    • 4 Videos
    • 1 Discussion
    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Practice Quiz

1 Discussions

  • Finding your own prepositional phrase attachment

1 Labs

  • Module 2

4 Videos

  • Basic Natural Language Processing
  • Basic NLP tasks with NLTK
  • Advanced NLP tasks with NLTK
  • Application: Spell Checker

Week 2 - Assignments

    • 1 Programming
    • 1 Assignment
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1 Programming

  • Assignment 2

1 Assignment

  • Module 2 Quiz

Module 3: Classification of Text

    • 7 Videos
    • 1 Lab
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1 Labs

  • Case Study - Sentiment Analysis

7 Videos

  • Text Classification
  • Identifying Features from Text
  • Naive Bayes Classifiers
  • Naive Bayes Variations
  • Support Vector Machines
  • Learning Text Classifiers in Python
  • Demonstration: Case Study - Sentiment Analysis

Week 3 - Assignments

    • 1 Programming
    • 1 Assignment
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1 Programming

  • Assignment 3

1 Assignment

  • Module 3 Quiz

Module 4: Topic Modeling

    • 4 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz

4 Videos

  • Semantic Text Similarity
  • Topic Modeling
  • Generative Models and LDA
  • Information Extraction

1 Readings

  • Additional Resources & Readings

Week 4 - Assignments

    • 1 Programming
    • 1 Assignment
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1 Programming

  • Assignment 4

1 Assignment

  • Module 4 Quiz

Post-Course Survey

    • 3 Readings
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3 Readings

  • Post-Course Survey
  • Keep Learning with Michigan Online
  • Course 4 complete! ✔️ Time to celebrate

Auto Summary

"Applied Text Mining in Python" is a professional-level course perfect for those in the Data Science & AI domain. Taught by Coursera, it spans 1500 minutes and covers text mining, manipulation, and natural language processing using Python. The curriculum includes basic to advanced techniques like text classification and topic modeling. Ideal for learners with prior knowledge in Data Science, Plotting, and Machine Learning. Subscription options include Starter, Professional, and Paid plans.

V. G. Vinod Vydiswaran
Instructor

V. G. Vinod Vydiswaran