We used "Abstractive Text Summarization" approach to identify the important sections, interpret the context and reproduce in a new way. This ensures that the core information is conveyed through the shortest text possible, the sentences in summary are generated, not just extracted from the original text.
Is the model able to summarize the text while retaining the most important information?
The dataset is about text news and was downloaded from the Kaggle website. It contains 98401 observations.
- Pandas
- NumPy
- SQLAlchemy
- Sklearn
- Seaborn
- matplotlib
- Tableau
- Flask
- Heroku
- Plotly
- nltk
- contractions
- re
- tensorflow
- Keras