Training a NAMED ENTITY RECOGNITION MODEL with Prodigy and Transfer Learning

Prodigy is a modern annotation tool for collecting training data for machine learning models, developed by the makers of spaCy. In this video, we'll show you how to use Prodigy to train a named entity recognition model from scratch, by taking advantage of semi-automatic annotation and modern transfer learning techniques.
STEP BY STEP
03:24 - Create a phrase list and match patterns for ingredients
09:24 - Label all ingredients in a sample of texts from r/Cooking with the help of match patterns
19:25 - Train and evaluate a first model to see if we're on the right track
24:44 - Label more examples by correcting the model's predictions
31:56 - Train a new model with improved accuracy
34:11 - Run model over 2m+ Reddit comments and count the mentions over time
37:00 - Select interesting results and visualize them
PRODIGY
● Website & docs: prodi.gy
● Live demo: prodi.gy/demo
● Forum: support.prodi.gy
● Recipe scripts: github.com/exp...
THIS TUTORIAL
● Code & data: github.com/exp...
● Visualization: public.flouris...
● Download Reddit comments: files.pushshif...
● spaCy documentation: spacy.io
FOLLOW US
● Ines Montani: / _inesmontani
● Explosion: / explosion_ai
CREDITS
● Food emoji: github.com/twi...