phlippe/uvadlc_notebooks

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

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These Jupyter notebook tutorials help you understand complex deep learning theories by showing their practical implementations. You'll work with code examples that illustrate concepts like transformers and graph neural networks, gaining hands-on experience with frameworks like PyTorch and JAX+Flax. This resource is for master's students in Artificial Intelligence, particularly those taking the Deep Learning Course at the University of Amsterdam, to deepen their comprehension of lecture material.

3,111 stars.

Use this if you are a student or practitioner looking to connect deep learning theoretical concepts with practical code implementations, especially within the PyTorch or JAX+Flax frameworks.

Not ideal if you are looking for a standalone deep learning course with no prior theoretical background, or if you need to train very large models on advanced GPU clusters without modification.

deep-learning-education artificial-intelligence-curriculum neural-network-implementation machine-learning-tutorials pytorch-jax-training
No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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674

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Jupyter Notebook

License

MIT

Last pushed

Oct 31, 2025

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