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 Visit our podcasts homepage for transcripts and more episodes! www.wandb.com/podcast Get our podcast on Apple, Spotify, and Google! Apple Podcasts: bit.ly/2WdrUvI Spotify: bit.ly/2SqtadF Google:tiny.cc/GD_Google We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it! Join our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research: tiny.cc/wb-salon Join our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning: bit.ly/wb-slack Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices. app.wandb.ai/gallery