The Conference for Machine Learning Innovation

Using Neural Networks for Natural Language Processing

Session
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Join the ML Revolution!
Register until the conference starts:
✓ 50% off on all prices
✓ 10% team discount
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Join the ML Revolution!
Register until November 4:
✓ 2 in 1 conference special
✓ Save up to €220
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until November 4:
✓ 2 in 1 conference special
✓ Save up to €220
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now
Infos

Thanks to Transformer Architectures like BERT and GPT-2, we have recently experienced the “ImageNet Moment” for Natural Language Processing (NLP). Like with Computer Vision benchmarks eight years ago, the results for various NLP tasks have improved significantly in a very short amount of time. But how to train a neural network to deal with language, with its varying input length and non-numerical data? How to compare the flat output tensor of a neural network with an expected syntax tree to compute a loss? In this talk, we will look at ways to feed language into a neural network and how to interpret its output for various common NLP tasks, like classification, sentiment analysis, Part-of-Speech (POS) tagging, Named Entity Recognition (NER) and coreference resolution. We will also see how the output of a network needs to be interpreted to create completely new text. The talk will be accompanied by real world examples based on Transformer Architectures.

This Session originates from the archive of Diese Session stammt aus dem Archiv von SingaporeSingapore . 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 SingaporeSingapore . 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 SingaporeSingapore . 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 SingaporeSingapore . 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