Applied Natural Language Processing
Join the wold’s largest applied NLP community at the virtual NLP Summit 2022! Three days of immersive, industry-focused content including over 50 technical sessions, with focus days on open source, healthcare, and finance. Join live Q&A sessions with the speakers, connect with others through networking features, and access all content on-demand after the event.
The second week will feature beginner to advanced live training workshops with certifications. Learn, share, and apply best practices for putting AI to good use!
Speakers
Moran Beladev
Data Science Team Leader at Diagnostic Robotics
Omri Allouche
Head of Research at Gong.io
Isaac Palka
Senior Director of Engineering at Invitae
Sakshi Bhargava
Staff Data Scientist at Chegg
Barret Zoph
Staff Research Scientist at Google Brain
Liam Fedus
Senior Research Scientist at Google Brain
Lena Pfitzer
Principal Data Scientist at myNEO
Carlos Morato
VP of Applied Science & Artificial Intelligence at Optum
Giancarlo Crocetti
Professor at St. John's University & Capability Lead of Data Science & AI Enablement at Boehringer Ingelheim
About
The NLP Summit is the gathering place for those putting state-of-the-art natural language processing to good use. This third edition of the virtual conference showcases NLP best practices, real-world case studies, challenges in applying deep learning & transfer learning in practice – and the latest open source libraries, models & transformers you can use today. The NLP Summit brings together the growing NLP community interested in building language understanding applications used in healthcare, life science, finance, eCommerce, media, recruiting, and more.
Topics Covered
- Scaling NLP pipelines
- Machine translation in practice
- De-identification of sensitive free-text data
- Speech-to-text models and applications
- Ethical issues in natural language processing
- Object character recognition (OCR)
- Applications of natural language generation
- Tuning transformers for domain-specific NLP
- Optimizations & benchmarks on deep learning chips
- Multi-lingual NLP models and applications
- Question answering systems
- Conversational AI and dialog systems
- Building knowledge graphs from large document repositories
- Comparing BERT, Albert, Roberta, Ernie & friends
- Applying the “pre-train and fine-tune” paradigm
- Clinical natural language understanding
- Information extraction from natural language documents