How to Easily Find Keywords in a Document with KeyBERT in Python

📚 What You'll Learn:

Introduction to KeyBERT: Understand what KeyBERT is and why it's a valuable tool for digital humanities.
Installation and Setup: Learn how to install KeyBERT and set it up with the transformer model of your choice.
Preparing Texts: We'll walk you through preparing three different texts for analysis.
Extracting Keywords with KeyBERT: Dive into the code to extract keywords from each text using the KeyBERT model.
Conclusion & Further Exploration: Wrap up the lesson and explore how you can customize KeyBERT for your research.

📖 Ideal for Digital Humanists:
This tutorial is tailored for digital humanists who want to explore key themes, characters, or ideas in textual data. Whether you're working with literary classics or contemporary texts, KeyBERT can help you uncover the essence of the text.

🔗 Resources & Links:

Join this channel to get access to perks:

If you enjoy this video, please subscribe.

If there's a specific video you would like to see or a tutorial series, let me know in the comments and I will try and make it.

You can follow me at:

[sebastianpranz]

Thank you for sharing! Awesome tool, I have trillions of use cases in mind … think I'll start with auto-tagging my pdf library …

[jakobkristensen]

Great explanation! But what are some actual usecases for this? Thanks

[daryladhityahenry]

Hi! I kind of curious... Is there any context size limit for these kind? keybert, bertopic? If not, isn't they kind of superior vs current GPT? Event though the use case is different, but in someway, it has the upperhand. Like this one, getting keyword, or bertopic to get topic model. GPT can't even do that because the context size is limited and can forget the middle part of the article..

And if there's no context size limit, so it can be like our library? We can collect so much data, and when we need, we can search using this... Or explore using topic modelling to find out better what we want. Am I right?

Thanks..

[sureshkumargondi]

Super easy to understand this. Thanks for making the video.

Quick question, Can we argument these generated keywords to generate questions too? If we can, ..then how we can do?

Thank you in advance.

[jesusmtz]

Do you have a video on fine-tuning with sentence transformers? I have text which is very narrow in domain with a lot of typos and weird jargon. But I do have identified the key features to extract. Thanks

[tarik]

Hello thanks for thé vidéo dumb question if it IS bert based does it have thé same limitation in term of thé text size?

[xinlongzhang-th]

Hello, sorry to bother you! I want to ask you a question about the usage of Keybert. I create a excel file which contains thousands of texts, how can I extract keywords from this excel file?Thanks a lot!

[sriram]

I am unable to run even a sample code in my work setup !!
I am facing some SSL errors for which I couldn't find a reliable solution.