m2dsupsdlclass/lectures-labs resource

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1470 stars · 661 forks observed · 2026-08-28

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

A collection of lecture slides and Jupyter lab notebooks for a Master Year 2 Data Science Deep Learning course at Institut Polytechnique de Paris. It covers neural networks, backpropagation, CNNs, RNNs, NLP, generative models, and more, with hands-on exercises built on Keras and TensorFlow.

Use cases

• learn deep learning from scratch with slides and labs
• practice backpropagation with numpy notebooks
• study convolutional neural networks for image classification
• learn sequence-to-sequence models and attention
• find course materials on unsupervised and generative deep learning
• run deep learning labs in binder with keras and tensorflow

When to choose

• you want structured university-level deep learning course material
• you prefer learning through hands-on Jupyter notebooks with solutions
• you want coverage of both computer vision and NLP topics
• you use Keras/TensorFlow as your deep learning framework

When to avoid

• you need PyTorch-based course materials
• you want production deep learning tooling rather than educational content
• you need up-to-date coverage of transformer-based LLMs

Facets

learning-resource · maturity active

deep-learning machine-learning nlp computer-vision deep-learning machine-learning education tutorials python cross-platform jupyter-notebooks lecture-slides keras tensorflow university-course ip-paris

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