Simple Text Summarization using TF-IDF Vectorizer | Machine Learning | Project Shop

The Simple Text Summarization using TF-IDF (Term Frequency-Inverse Document Frequency) Vectorizer project is a text-based machine learning project that aims to develop a model capable of summarizing a long paragraph into a required number of sentences. Providing the long paragraph and no.of.lines needed for output, the model can summarize the paragraph. The TF-IDF-based approach relies on the quality of TF-IDF scoring. If the scoring is accurate, it should favor sentences that contain essential information. It’s important to note that while TF-IDF-based extractive summarization is a simple and interpretable technique, it may not capture nuanced relationships in the text as effectively as more advanced techniques like abstractive summarization or neural models. The trustworthiness of the output should be evaluated in the context of the specific task and its requirements.

Project Explanation, Requirements, and Project setup details are given inside the project folder.