Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Mohamed AbdelHady

Mohamed AbdelHady
Senior Data Scientist, Microsoft

Mohamed AbdelHady is a senior data scientist on the algorithms and data science (ADS) team within the AI+R Group at Microsoft, where he focuses on machine learning applications for text analytics and natural language processing. Mohamed works with Microsoft product teams and external customers to deliver advanced technologies that extract useful and actionable insights from unstructured free text such as search queries, social network messages, product reviews, customer feedback. Previously, he spent three years at Microsoft Research’s Advanced Technology Labs. He holds a PhD in machine learning from the University of Ulm in Germany.

Sessions

2:40pm–3:20pm Wednesday, March 7, 2018
Deep learning for domain-specific entity extraction from unstructured text
Big data and data science in the cloud, Data science and machine learning
 Location: LL21 B
Mohamed AbdelHady (Microsoft), Zoran Dzunic (Microsoft)
Average rating: ***..
(3.50, 2 ratings)
Mohamed AbdelHady and Zoran Dzunic demonstrate how to build a domain-specific entity extraction system from unstructured text using deep learning. In the model, domain-specific word embedding vectors are trained on a Spark cluster using millions of PubMed abstracts and then used as features to train a LSTM recurrent neural network for entity extraction. Read more.