The Conference for Machine Learning Innovation

From Paper to Product – How we implemented BERT

Session
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Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
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!
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
Infos

BERT is a state-of-the-art natural language processing (NLP) model that allows pretraining on unlabelled text data and later transfer training to a variety of NLP tasks. Due to its promising novel ideas and impressive performance we chose it as a core component for a new natural language generation product. Reading a paper, maybe following a tutorial with example code and putting a working piece of software into production are, however, two totally different things.

In this session, we will tell you how we trained a custom version of the BERT network and included it into a natural language generation (NLG) application. You will hear how we arrived at the decision to use BERT and what other approaches we tried. We will tell you about the failures and the mistakes we made so you do not have to repeat them, but also about the surprises, successes and lessons learned.

This Session originates from the archive of Diese Session stammt aus dem Archiv von BerlinBerlin . Take me to the program of . Hier geht es zum aktuellen Programm von Singapore Singapore .

This Session originates from the archive of Diese Session stammt aus dem Archiv von BerlinBerlin . Take me to the program of . Hier geht es zum aktuellen Programm von Berlin Berlin .

This Session originates from the archive of Diese Session stammt aus dem Archiv von BerlinBerlin . Take me to the program of . Hier geht es zum aktuellen Programm von Munich Munich .

This Session Diese Session originates from the archive of stammt aus dem Archiv von BerlinBerlin . Take me to the current program of . Hier geht es zum aktuellen Programm von Singapore Singapore , Berlin Berlin or oder Munich Munich .

Behind the Tracks