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Learning Deep Learning with PyTorch (3) Knowing PyTorch
This workshop series is to present overviews to the exciting deep learning techniques and to provide a practical guide for general audience to step into the field. It will be primarily appropriate for the beginners who want to learn the techniques and apply to their future research activities. Researchers with deep learning experiences are expected to get benefits from related discussions as well.
In the third session of the series, we will introduce PyTorch deep learning framework, illustrate the basic usage of tensors and automatic differentiation, and solve a simple temerature-conversion problem using PyTorch. The knowledge of topics covered in the first and second session about machine/deep learning is assumed. Working experience of Python, Jupyter Notebooks will be helpful to follow the demos.
If you have any further questions regarding the workshop, please contact instructor Qiyang Hu.
Please REGISTER to the Zoom Meeting before joining.