Since the beginning of COVID outbreak, numerous papers have been written describing related medical research, many of which are available in CORD dataset. In this talk, we will describe our experiment of applying Open Domain Question Answering model to this dataset using recent BERT model available in DeepPavlov NLP framework. We will also demonstrate how this model can be trained in a cost-effective manner on Azure Machine Learning, using different compute options for data preparation and training.

Instructor's Bio

Mikhail Burtsev Ph.D.

Head of Neural Networks and Deep Learning Lab at MIPT, Founder of DeepPavlov

Experienced Head of Deep Learning research projects with a demonstrated history of working in the research institutions. Skilled in Neural Networks, Mathematical Modeling, Python, Computer Science, Cognitive Science, and Genetic Algorithms. Strong research professional with a Doctor of Philosophy (Ph.D.) focused in Artificial Intelligence.

Dmitry Soshnikov Ph.D.

Cloud Developer Advocate at Microsoft, Associate Professor at MIPT

Dmitry is Cloud Developer Advocate for Microsoft, specializing in AI/ML and F#. He also teaches AI and Functional/Logic Programming at top Moscow Universities. Passionate father, Digital Artist, Gun Fu Cha master, etc.

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    BERT-based Open Domain Question Answering using DeepPavlov Library on Azure Machine Learning

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