Extracting Text Meaning using TF-IDF
Curso
443 Estudiantes ya inscritos- Gain proficiency in summarizing texts by calculating TF-ISF scores.
- Grasp the concept of tokenizing sentences and words for text analysis.
- Understand how to remove unnecessary headers and footers from text data.
- Identify and utilize the top N sentences in a body of text based on their significance.
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This project focuses on the design and implementation of a robust text summarizer, built using Python. By harnessing the capabilities of Python’s Natural Language Toolkit (NLTK), participants will gain hands-on experience in processing and analyzing textual data. The project covers a range of NLP techniques essential for text summarization. Participants will develop skills in parsing text and extracting meaningful content, learning how to filter essential information from large volumes of text.- IntroductionVista previa
- Import NLTKVista previa
- Load Text DataVista previa
- Remove Header and FooterVista previa
- Tokenize SentencesVista previa
- Tokenize WordsVista previa
- TF ScoreVista previa
- Words FrequencyVista previa
- ISF ScoreVista previa
- TF-ISF ScoreVista previa
- Score SentencesVista previa
- Top N SentencesVista previa
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Olha Drahomeretska
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Revisado en Jun 19, 2025
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