Understanding the intent of a natural language search is a major component of any natural language processing system. Although there are numerous machine learning and deep learning techniques to solve complex problems in natural language processing, such as understanding intent also known as natural language understanding, very few of them discuss the challenges in production. In this session we take you on a journey from development to production of natural language understanding component of Splunk Natural Language Platform. We will discuss several engineering and data science challenges, and also provide holistic approaches to overcome those challenges. Attendees of the session should walk away with a deeper understanding of different state-of-the-art techniques, such as understanding the intent of a natural language search query, that can help them build their own applications in the natural language processing domain.

Speaker(s)
Aungon Nag Radon, Sr. Data Scientist, Splunk
Anand Srinivasabagavathar, Senior Software Engineer, Splunk

Slides PDF link - https://conf.splunk.com/files/2019/slides/FN1716.pdf?podcast=1577146229