In this episode of PyDataSci, we’re joined by Ines Montani, Co-founder of Explosion, Co-developer of SpaCy and lead developer of Prodigy.
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Ines and I caught up to discuss her various projects, including the aforementioned SpaCy, an open-source NLP library built with a focus on industry and production use cases. In our conversation, Ines gives us an overview of the SpaCy Library, a look at some of the use cases that excite her, and the Spacy community and contributors. We also discuss her work with Prodigy, an annotation service tool that uses continuous active learning to train models, and finally, what other exciting projects she is working on.
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Thanks to our Sponsor!
I’d like to send a huge thanks to our sponsor for this series, IBM. IBM has a long history of engaging in and supporting open source projects that are important to enterprise data science — projects like Hadoop, Spark, Jupyter, Kubernetes, and Kubeflow.
IBM also hosts the IBM Data Science Community, which is a place for enterprise data scientists looking to learn, share, and engage with their peers and industry renowned practitioners. There you’ll find informative tutorials and case studies, Q&As with leaders in the field, and a lively forum covering a variety of topics of interest to beginning and experienced data scientists.
Visit the IBM Data Science Community at ibm.com/community/datascience.
From the Interview
- Presentation: Practical transfer Learning for NLP with spaCy and Prodigy
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“More On That Later” by Lee Rosevere licensed under CC By 4.0