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Applicable bert

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Veröffentlicht am

PPT presented DPS(https://digitalproductschool.io/) week 8, at engineering weekly.
Explaining how BERT model can be used in industry.

Veröffentlicht in: Technologie
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Applicable bert

  1. 1. Applicable BERT Jiwon Kim Engineering Weekly 8
  2. 2. How can we apply SOTA NLP model to the specific domain?
  3. 3. Can BERT be used in a sentiment classification?
  4. 4. 1. conda create -n bert python pytorch pandas tqdm conda install -c anaconda scikit-learn (Just for safeness..) 1. pip install pytorch-pretrained-bert (Thank you hugging face 🤗) 1. Prepare your data 2. Fine-tune the model with your data Yes, of course Just your target data, e.g., Yelp polarity data
  5. 5. Can BERT be used in a Question-Answering?
  6. 6. Definitely feat, pragnakalp 1. conda create -n bert python pytorch pandas tqdm conda install -c anaconda scikit-learn (Just for safeness..) 1. pip install pytorch-pretrained-bert (Thank you hugging face 🤗) 1. Prepare your data 2. Fine-tune the model with your data
  7. 7. Can BERT be used in a chatbot?
  8. 8. 1. conda create -n bert python pytorch pandas tqdm conda install -c anaconda scikit-learn (Just for safeness..) 1. pip install pytorch-pretrained-bert (Thank you hugging face 🤗) 1. Prepare your data 2. Fine-tune the model with your data Again….
  9. 9. Definitely feat, pragnakalp
  10. 10. Can BERT be used in sentence auto-completion?
  11. 11. Gmail’s Suggested Replies, Smart Compose & Google Search Autocomplete What is autocompletion?
  12. 12. Sure you can use BERT! 1. conda create -n bert python pytorch pandas tqdm conda install -c anaconda scikit-learn (Just for safeness..) 1. pip install pytorch-pretrained-bert (Thank you hugging face 🤗) 1. Prepare your data 2. Fine-tune the model with your data feat, Hugging face
  13. 13. Why suddenly GPT-2???? 🤗🤗🤗🤗 🤗
  14. 14. € 40K
  15. 15. Review BERT can be used as ● Sentiment(emotion) classification ● Question-Answering ● Chatbot ● Sentence auto-completion
  16. 16. SO………. What is a BERT?
  17. 17. It would be way more long story…... Concepts that you should know... ● Transformer, ELMo, GPT ● Transfer Learning from Supervised Data ● Embedding model(position embedding, segment embedding, token embedding) ● Pre-trained model ● Attention mechanism(e.g., Scaled Dot-Product Attention Multi-Head Attention) ● Semi-supervised sequence learning ● Position-wise Feed-Forward Networks ● And so on…... Paper link 1 Paper link 2
  18. 18. Henry AI Labs
  19. 19. ● BERT can be used at least…. ○ Sentiment(emotion) classification ○ Question-Answering ○ Chatbot ○ Sentence auto-completion ● Feel free to ask me if you can’t find out the pre-made code. ● “Don’t try to understand everything what you use… just run the code, and don’t go deep on theory.” - Jeremy Howard ● Still you want to understand theoretical background, let’s study. Conclusion

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