dataflowr/notebooks
Jupyter notebooks and code for a university deep learning course at École Polytechnique covering neural networks, PyTorch, and model fine-tuning.
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This repository provides educational materials for a deep learning course taught at École Polytechnique. The content includes interactive Jupyter notebooks covering topics such as neural network implementation from scratch, PyTorch tensor operations, automatic differentiation, and transfer learning with pretrained models like VGG. Students work through practical exercises on classification tasks, MLPs, and autodiff concepts.
Frequently asked
- What is dataflowr/notebooks?
- Jupyter notebooks and code for a university deep learning course at École Polytechnique covering neural networks, PyTorch, and model fine-tuning.
- Is notebooks open source?
- Yes — dataflowr/notebooks is open source, released under the Apache-2.0 license.
- What language is notebooks written in?
- dataflowr/notebooks is primarily written in Jupyter Notebook.
- How popular is notebooks?
- dataflowr/notebooks has 1.3k stars on GitHub.
- Where can I find notebooks?
- dataflowr/notebooks is on GitHub at https://github.com/dataflowr/notebooks.