Deep Learning in Geoscience Applications with Shell’s Team Lead

Presented by Hewlett Packard Enterprise Data Science Institute and the Geophysical Society of Houston

The HPE Data Science Institute and the Geophysical Society of Houston delivered a webinar that explored the multilayered aspects of deep learning within geoscience applications.

Pandu Devarakota, team lead for Subsurface and Wells at Shell, discussed the distinctive tactics that could be utilized to benefit research when exploring deep learning, such as the application of image analysis. Not only has image analysis made significant contributions in the area of deep learning, it has left an impact on the expansion of geoscience.

Devarakota and his team work on projects pertaining to machine learning, deep learning and more. He revealed how to integrate certain methods into multi-task learning, which is a part of machine learning.

Along with techniques, Devarakota mentioned the tools an individual can use to expand their studies when dealing with artificial intelligence. Shell possesses an effective Artificial Intelligence initiative that has contributed to the enhancements of AI. The initiative, along with the deep learning techniques and tools Devarakota discussed, will continue to create a long-lasting impact in the area of data science.

Author

Eno Oduok

Source Name

HPE Data Science

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