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Put AI to Work
April 29-30, 2018: Training
April 30-May 2, 2018: Tutorials & Conference
New York, NY
Mustafa Kabul

Mustafa Kabul
Senior Data Scientist, SAS

Mustafa Kabul is a data scientist in the Analytic Server Division of R&D at SAS, where he leads innovative projects for SAS’s next-generation AI-enabled analytics products, including applications of deep learning. His current focus is on applying deep reinforcement learning to operational problems in the CRM and IoT spaces. An operations research expert working at the interface of machine learning and optimization, previously, he developed distributed, large-scale integer optimization algorithms for marketing optimization problems. Ever the optimization enthusiast, Mustafa always looks into ways to improve the algorithms. Nowadays his favorites are the distributed stochastic gradient and online learning methods. Mustafa holds a PhD from the University of North Carolina at Chapel Hill, where his research focused on game theory models of supply chains selling to strategic customers.

Sessions

11:55am–12:35pm Tuesday, May 1, 2018
Long-term time series forecasting with recurrent neural networks
Implementing AI, Models and Methods
 Location: Grand Ballroom West
Mustafa Kabul (SAS)
Average rating: ****.
(4.00, 3 ratings)
Forecasting the long-term values of time series data is crucial for planning. But how do you make use of a recurrent neural network when you want to compute an accurate long-term forecast? How can you capture short- and long-term seasonality or discover small patterns from the data that generate the big picture? Mustafa Kabul shares a scalable technique addressing these questions. Read more.