Sofie and Ines walk us through how the new spaCy library helps build end to end SOTA natural language processing workflows.

Ines Montani is the co-founder of Explosion AI, a digital studio specializing in tools for AI technology. She's a core developer of spaCy, one of the leading open-source libraries for Natural Language Processing in Python and Prodigy, a new data annotation tool powered by active learning. Before founding Explosion AI, she was a freelance front-end developer and strategist.
https://twitter.com/_inesmontani

Sofie Van Landeghem is a Natural Language Processing and Machine Learning engineer at Explosion.ai. She is a Software Engineer at heart, with an absurd love for quality assurance and testing, introducing proper levels of abstraction, and ensuring code robustness and modularity.

She has more than 12 years of experience in Natural Language Processing and Machine Learning, including in the pharmaceutical industry and the food industry.
https://twitter.com/oxykodit

https://spacy.io/
https://prodi.gy/
https://thinc.ai/
https://explosion.ai/

Topics covered:
0:00 Sneak peek
0:35 intro
2:29 How spaCy was started
6:11 Business model, open source
9:55 What was spaCy designed to solve?
12:23 advances in NLP and modern practices in industry
17:19 what differentiates spaCy from a more research focused NLP library?
19:28 Multi-lingual/domain specific support
23:52 spaCy V3 configuration
28:16 Thoughts on Python, Syphon, other programming languages for ML
33:45 Making things clear and reproducible
37:30 prodigy and getting good training data
44:09 most underrated aspect of ML
51:00 hardest part of putting models into production

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