Microsoft Reactor

What is this session about?
In this talk, we will first give an overview of how question-answering techniques work in NLP. We will then showcase a submitted solution for Kaggle COVID-19 Open Research Dataset Challenge (CORD) with an overview of the competition format, followed by describing the code combined of using the word embedding and fine-tuning BERT. We will discuss the results at the end.

Who is it aimed at?
The session is aimed at new data scientists with some introductory level of NLP and also established data scientists interested in developing QA applications.

Why should I attend?
If you wish to learn more on the following technologies or techniques this is the session for you:
· Question-Answering in NLP
· Word2Vec Embedding
· Fine-Tuning BERT Language Model

For more on this series, visit https://developer.microsoft.com/en-us/reactor/eventseries/NaturalLanguage

Speaker info:
Lida Ghahremanlou - Cloud Solution Architect - Microsoft

Dr. Lida Ghahremanlou is an AI specialist and a Cloud Solution Architect at Microsoft, Data & AI Azure team from Customer Success Unit (CSU), working closely with customers and partners on providing AI and Machine learning solutions using Azure cloud technologies. Prior to joining Microsoft, she was a research scientist at IBM-Research in Australia where her focus was on Cognitive Computing and Semantic Technologies. Lida is passionate in applying her skills and experience within NLP applications and solving real world problems of language understanding.

Paolo Colecchia – Senior Cloud Solution Architect – Microsoft

Paolo Colecchia is an AI & ML specialist within the Azure Data & AI team at Microsoft. He works very closely with customers and partners across several industries to architect, develop and deploy AI solutions at scale. Paolo has a strong passion in applying data science skills within the Deep Learning space with particular focus on NLP solutions