Deep Learning in Julia

Deep Learning In Julia

by Hanyang Chen

Deep learning is the most heated paradigm in artificial intelligence. Its tsunami sweeps from natural language to image processing, from automated robots to knowledge reasoning.
Julia is an uprising high-performance computing language. Only developed in four years, it is steady absorbing harsh users who require both neat expression and efficient consumption.

The presentation starts with the historical development of deep learning followed by the introduction of using Julia's MXNet deep learning package. Comparisons of several Julia packages for deep learning will also be covered. The detailed outline will follow soon.

Presenter's bio:
Hanyang Chen is a Ph.D. student in UCD, supervised by Dr. Tony Veale. He focuses on metaphor-generating algorithms in natural language processing(NLP), while he is also interested in machine learning and knowledge engineering. Before he started his Ph.D., he received his B.Sc. degrees at Fudan University and UCD in 2014, working on deep learning approaches in Chinese word segmentation and sentence parsing.