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

Patrick Harrison
Associate Director, Data Science, S&P Global

@skipgram

Patrick Harrison started and leads the data science team at S&P Global Market Intelligence (S&P MI), a business and financial intelligence firm and data provider. The team employs a wide variety of data science tools and techniques, including machine learning, natural language processing, recommender systems, graph analytics, among others. Patrick is the coauthor of the forthcoming book Deep Learning with Text from O’Reilly Media, along with Matthew Honnibal, creator of spaCy, the industrial-strength natural language processing software library, and is a founding organizer of a machine learning conference in Charlottesville, Virginia. He is actively involved in building both regional and global data science communities. Patrick holds a BA in economics and an MS in systems engineering, both from the University of Virginia. His graduate research focused on complex systems and agent-based modeling.

Sessions

2:40pm3:20pm Thursday, March 8, 2018
Data science and machine learning
Location: LL21 B Level: Intermediate
Patrick Harrison (S&P Global)
Average rating: ****.
(4.33, 3 ratings)
Word vector embeddings are everywhere, but relatively few understand how they produce their remarkable results. Patrick Harrison opens up the black box of a popular word embedding algorithm and walks you through how it works its magic. Patrick also covers core neural network concepts, including hidden layers, loss gradients, backpropagation, and more. Read more.