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: https://prodi.gy ● Live demo: https://prodi.gy/demo ● Forum: https://support.prodi.gy ● Recipe scripts: https://github.com/explosion/prodigy-... THIS TUTORIAL ● Code & data: https://github.com/explosion/projects... ● Visualization: https://public.flourish.studio/visual... ● Download Reddit comments: https://files.pushshift.io/reddit/com... ● spaCy documentation: https://spacy.io FOLLOW US ● Ines Montani:   / _inesmontani   ● Explosion:   / explosion_ai   CREDITS ● Food emoji: https://github.com/twitter/twemoji