Anthill Inside 2017

On theory and concepts in Machine Learning, Deep Learning and Artificial Intelligence. Formerly Deep Learning Conf.

Gaurav Goswami


Getting Started with GPU Accelerated Deep Learning

Submitted Jul 10, 2017

Deep learning has been applied to various domains with great success and is a popular technique to solve challenging machine learning problems in the real world. However, deep learning is also computationally expensive and it is not feasible to train a deep network in a reasonable time frame on large databases without using GPU acceleration. In this talk, I will provide a tutorial on how to setup the pre-requisite drivers, packages, and tools to get started with GPU enabled deep learning on a machine running Ubuntu OS. In addition, we will take a quick look at running a deep learning workload on the GPU via a Jupyter notebook and conclude with an overview of the performance difference when using a CPU vs GPU for deep learning.


Draft slides are available here: I will update these to the full version soon. I would ideally like to showcase aspects of the workflow including the workload notebook live in action during the talk.

Speaker bio

I am currently working at IBM India as an Artificial Intelligence/Machine Learning expert. My Ph.D. thesis focuses on using machine learning and computer vision techniques to solve challenges in face recognition by improving the computation and combination of robust representations. I have had the opportunity to be a part of crafting a machine learning based solution for real world use cases in these domains.




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