The Conference for Machine Learning Innovation

Introduction to Sentence Embeddings

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Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
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Register until November 03:
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✓ 10% Team Discount
✓ Special discount for freelancers
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Join the ML Revolution!
Register until November 03:
✓ Save up to €494
✓ 10% Team Discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now

Language models like BERT (an others based on transfer learning) have created an enormous interest in natural language processing (NLP) during the last years. As a recent application, we want to introduce sentence embeddings in this talk. They can be implemented easily and are very useful for a variety of applications. Details can be found on sbert.net.

In the talk, we will focus on the theory shortly and then turn to applications with examples for re-ranking, cross-encoders and comparing meaning of sentences across different languages.

Combined with other methods, sentence embeddings can be used to automatically classify unlabeled data or extend partially categorized data. We will explain both use cases. We encounter both scenarios frequently in our own projects and so far they could only be solved with considerable manual effort.

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