How to Build a Question Answering Application with Haystack in 30 Minutes
Are you planning to build your own question answering application but don’t know where to start? In this talk, Julian Risch will walk you through the steps of creating a demo around public health data using the open source NLP framework Haystack. The key building blocks of Haystack support a variety of semantic search pipelines, and he will explain how they can be flexibly combined to enable different use cases. An outlook on what could come next, once you have a running demo, will conclude the presentation.
Senior Machine Learning Engineer at Deepset
Julian Risch is a senior machine learning engineer at deepset, where he implements the open source neural search framework Haystack and bridges the gap between academic research and industry applications. He holds a PhD from the University of Potsdam’s Hasso Plattner Institute, and his research interests include deep learning, text classification, and question answering. When he is not working on making computers understand humans, you can find him organizing the Open NLP Meetup event series.