Extractive text summerization source for ref = https://www.analyticsvidhya.com/blog/2019/06/comprehensive-guide-text-summarization-using-deep-learning-python/

Extractive Summarization =>

The name gives away what this approach does. We identify the important sentences or phrases from the original text and extract only those from the text. Those extracted sentences would be our summary.

Abstractive Summarization =>

This is a very interesting approach. Here, we generate new sentences from the original text. This is in contrast to the extractive approach we saw earlier where we used only the sentences that were present. The sentences generated through abstractive summarization might not be present in the original text

ref = https://medium.com/intel-student-ambassadors/diving-into-abstractive-text-summarization-part-1-e8570d370021

https://machinelearningmastery.com/develop-encoder-decoder-model-sequence-sequence-prediction-keras/