Webinar series
Snorkel Flow live demo
September 15, 2022 | 11:00 AM - 11:45 AM Pacific Time
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Join us for a live demonstration of Snorkel Flow, the data-centric AI development platform used by Fortune 500 enterprises and government agencies to accelerate their AI development by 10-100x. Snorkel Flow can be used to classify and extract information from unstructured text like documents and social media, semi-structured text such as PDFs, and webpages, and structured text or numeric data.
In this webinar, Braden Hancock, Snorkel AI Co-founder and Head of Technology, will build a text classification application based on a real-world financial services use case with a Fortune 50 bank and answer live questions.
Join us to see how Snorkel Flow:
- Accelerates AI development with programmatic labeling, a fundamentally more scalable approach to building and maintaining high quality datasets
- Enables utilizing existing resources (noisy labels, models, ontologies, etc.), domain expert heuristics, embeddings, foundation models and more to improve label quality
- Continuously updates and analyzes models to guide training data development
- Enables adapting to real-world changes with a few clicks instead of manual relabeling from scratch
- Provides transparency around where your training labels are coming from and how to update or correct them to improve model performance
- Supports one-click deployment of trained models in sealed application packages that can be run locally or transferred to your production environment
Space at this event is limited to enterprise users and advance registration with a business email is required. Your registration request will be reviewed by the Snorkel team and you will receive an email confirmation from Zoom once approved to attend the live event. Registration will close 24 hours prior to the event.
Presented by
Braden Hancock
Co-founder and Head of Technology
Snorkel AI
About the presenter
Braden Hancock
Braden is a co-founder and Head of Technology at Snorkel AI. Before Snorkel, Braden researched and developed new interfaces to machine learning systems in academia (Stanford, MIT, Johns Hopkins, BYU) and industry (Facebook, Google).
We look forward to seeing you!
Register now