dataflowr/notebooks resource

Health v2 · maintenance only

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1268 stars · 333 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Jupyter notebook code and practicals for the Dataflowr 'Deep Learning DIY' course, covering PyTorch tensors, autodiff, CNNs, optimization, and more. It accompanies the free online course taught at École Polytechnique, with solutions to all practicals.

Use cases

• learn deep learning from scratch with pytorch
• find practical exercises for training neural networks
• understand automatic differentiation and backpropagation
• study convolutional neural networks with worked notebooks
• self-study a university-level deep learning course
• reproduce experiments from recent deep learning papers

When to choose

• you want a structured, hands-on PyTorch course with solutions
• you prefer learning through notebooks rather than high-level APIs
• you need free course material runnable on Colab without a GPU

When to avoid

• you need a production deep learning framework or library
• you want TensorFlow or high-level API tutorials
• you need a maintained software package rather than course code

Facets

learning-resource · maturity active

deep-learning machine-learning developer-tools deep-learning machine-learning tutorials education python cross-platform pytorch jupyter-notebooks course-material dataflowr self-paced-learning

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For agents

markdown · JSON · MCP: product_card(name="dataflowr/notebooks")