Course Outline
Introduction to Text Summarization with Python for Government
- Comparing sample text with auto-generated summaries in government contexts
- Installing sumy (a Python Command-Line Executable for Text Summarization) for use in government applications
- Using sumy as a Command-Line Text Summarization Utility (Hands-On Exercise for Government)
Evaluating three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17 based on documented features and their suitability for government use
Choosing a library: sumy, pysummarization or readless for government applications
Creating a Python application using the sumy library on Python 2.7/3.3+ for government
- Installing the sumy library for Text Summarization in government systems
- Using the Edmundson (Extraction) method in the sumy Python Library for Text Summarization in government contexts
Summarization
- Creating simple Python test code that uses the sumy library to generate a text summary for government use
Creating a Python application using the pysummarization library on Python 2.7/3.3+ for government
- Installing the pysummarization library for Text Summarization in government systems
- Using the pysummarization library for Text Summarization in government applications
- Creating simple Python test code that uses the pysummarization library to generate a text summary for government use
Creating a Python application using the readless library on Python 2.7/3.3+ for government
- Installing the readless library for Text Summarization in government systems
- Using the readless library for Text Summarization in government applications
Creating simple Python test code that uses the readless library to generate a text summary for government use
Troubleshooting and debugging for government applications
Closing Remarks for Government Use
Requirements
- A working knowledge of Python programming (Python 2.7/3.3+)
- Familiarity with Python libraries in general, for government applications and projects
Testimonials (3)
The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)
Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI
Trainer develops training based on participant's pace
