phlippe/uvadlc_notebooks resource

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3181 stars · 682 forks observed · 2026-08-28

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

A collection of Jupyter notebook tutorials for the University of Amsterdam's MSc AI Deep Learning course, covering topics like optimization, transformers, and graph neural networks with implementations in PyTorch, PyTorch Lightning, and JAX/Flax. The notebooks are runnable on CPU laptops and are also published as official PyTorch Lightning tutorials.

Use cases

• learn deep learning concepts through hands-on notebook implementations
• understand how transformers work in PyTorch
• learn PyTorch Lightning with guided tutorials
• compare PyTorch and JAX/Flax implementations side by side
• study graph neural networks with runnable code
• prepare for a university deep learning course or exam

When to choose

• you want structured, course-quality tutorials with runnable code
• you prefer learning deep learning theory via implementations
• you want to learn PyTorch Lightning or JAX/Flax from worked examples
• you need tutorials that run on a CPU-only laptop

When to avoid

• you need production-ready deep learning code or a library
• you want a comprehensive reference rather than guided tutorials
• you need topics outside the course syllabus such as reinforcement learning or MLOps

Facets

learning-resource · maturity active

deep-learning machine-learning deep-learning tutorials education python jupyter-notebooks pytorch-lightning flax transformers graph-neural-networks university-course jax jupyter

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