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Recent advances in deep neural networks coupled with an increasing amount and complexity of scientific data collected in a wide array of domains provide many exciting opportunities for deep learning applications in scientific settings. Furthermore, libraries such as Google’s Tensorflow python library have made building deep learning models more accessible through common tools, freely available to researchers.
In this course, we’ll introduce some basic neural network and deep learning theory and give participants practical experience in some popular deep learning models and techniques.
There will be a significant practical element to the course and we will be working online in Google Colab notebooks.
Familiarity with python programming basics.
For queries relating to collaborating with the RSE team on projects: firstname.lastname@example.org
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