NLTK is widely used in the field of natural language processing because it offers a comprehensive toolkit for **processing and analyzing text data**, crucial for developing applications like sentiment analysis, topic identification, and text summarization.

To get started with NLTK in Python, you need to **import it** into your project. This can be done with a simple import statement: `import nltk`.

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.

We will be leveraging the powerful Natural Language Toolkit which is instrumental in the processing and analysis of textual data.

Extracting Text Meaning using TF-IDF

Import NLTK

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Extracting Text Meaning using TF-IDF

Import NLTK

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