Skip to collection list Skip to video grid
Skip to collection list Skip to video grid

USA: Day 2 - Hands-On Labs

Using Deep Learning for Entity Detection and Intent Extraction in Natural Language

Peter Izsak, Deep Learning Data Scientist, NLU Israel, AI Products Group, Intel In this session, we’ll get a glimpse into how algorithms can extract meaning out of our language. Entity detection and Intent extraction algorithms are key components in natural language understanding applications, such as, virtual assistants, chat-bots and information extraction systems. Recent Recurrent Neural Networks utilizing LSTMs and sequence tagging techniques helped us to improve the accuracy of the models compared to prior approaches. We will briefly present the tasks of named entity recognition and intent extraction, show best practices for developing deep learning based models for sequential tagging, and provide a hands-on demonstration of how to prepare, train and deploy such a model.

Read More
Read Less

categories

View more in
USA: Day 2 - Hands-On Labs

Currently loaded videos are 1 through 12 of 12 total videos.

First page loaded, no previous page available
Last page loaded, no next page available
Sort By:
Sort By: A-Z