upup is a graduate student in Computer Science at Peking University with nine years of hands-on software experience and a strong focus on deep learning implementation. They have actively ported the Dive into Deep Learning book from MXNet to PyTorch, contributing reproducible Jupyter Notebook implementations and practical data-operation solutions. Comfortable across the full stack of model development, upup blends academic rigor with applied engineering to bridge research code and usable PyTorch examples. Based in Beijing, they demonstrate a knack for translating textbook concepts into polished, open-source artifacts that help others learn and build.
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Role in this project:
Full-stack Developer
Contributions:231 commits, 22 PRs, 211 pushes in 1 year
Contributions summary:Upup primarily contributed to the implementation of deep learning models in the PyTorch framework within the context of the "Dive into Deep Learning" book. The commits focused on porting MXNet implementations to PyTorch, specifically addressing data operations and other basic concepts. The code changes involved the creation and modification of Jupyter Notebooks. The commit messages indicate a focus on reproducing and extending the material presented in the book using PyTorch.
Contributions:152 commits, 6 PRs, 158 pushes in 2 years 7 months
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upup - Student at WICT(http://www.wict.pku.edu.cn/)