How to Summarize Text Using Python and Machine Learning

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In this video we discuss several ways in which we can use recent advances in natural language processing and deep learning to summarize text. The techniques shown here have wide applications - from automatically extracting meaning from user reviews, to legal contract analysis, optimizing SEO strategies, financial analysis, extracting important information from electronic medical records, etc.

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This is the best video on summarizer! Thank u so much for such simplified explanation!

md.rezuwanhassan

Thank you Very much!
I followed all parts of this video completely and I got the better idea. But if you are voluntary to help us on abstractive text summarizations for less resourced local languages, it is best of all helps, for those are dealing with this issue, like me. Thank you again!

BinySD

Very helpful! Finally some video that helps!

lalithsasubilli

Thank you for this great tutorial, but I really want to ask some questions, do you know how to deal with the dead kernel when I downloading the model, pegasus_model =
And if you have time to reply my question, I really appreciate it. Thank you!

couples_I_like_are_real

Do I need to install pytorch and sentencpiece for pegasus?

rockpaper

Incredible video!! Do you know how can I solve this warning? in the summarization pipeline I still get only one phrase like in pegasus: UserWarning: Neither `max_length` nor `max_new_tokens` has been set, `max_length` will d `max_length` will default to 64 (`self.config.max_length`). Controlling `max_length` via the config is deprecated and `max_length` will be removed from the config in v5 of Transfnd using `max_new_toefault to 64 (`self.config.max_length`). Controlling `ormers -- we recommend using `max_new_tokens` to control the maximum length of the generation.

jaimebaquerizo