Video : Probabilistic time series forecasting & deep learning
On November 17 at the virtual Data Science Salon, Kashif Rasul, a research scientist at Zalando, gave a talk on deep learning for probabilistic time series forecasting. An interesting conference on the subject that we invite you to review.
Kashif Rasul, whose research interests include deep learning, reinforcement learning, and supercomputing, received his B.A. with honors from Monash University in Melbourne, Australia, and his Ph.D. in 2010 from the Free University of Berlin in the field of differential geometry and partial differential equations.
He completed his dissertation under the supervision of Professor Klaus Ecker. Before completing his PhD, he worked at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute) on the Cactus framework, an open source problem solving environment designed for scientists and engineers. Kashif Rasul has also worked as a software developer on Amira, a 3D scientific visualization framework. Finally, he is also the co-founder of two startups in the field of geospatial databases and crowdsourcing logistics.