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Learning Deep Learning with PyTorch (5) Data Augmentation and Transfer Learning
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 fifth session of the series, we will introduce data augmentation and transfer learning techniques to get a better solution for deep learning projects with PyTorch. The knowledge of topics covered in the previous sessions is assumed. Working experience of Python, Jupyter Notebooks and linear algebra will be helpful.
If you have any further questions regarding the workshop, please contact instructor Qiyang Hu.
Please REGISTER to the Zoom Meeting before joining.