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Ask HN: Project-Based Deep Learning Resources

1 points by bsuki ↗ HN
Hey all,

I found Replit's 100 Days of Code for Python, Andrej Karpathy's Zero to Hero, and Umar Jamil's coding transformers from scratch to be engaging resources because they were hands-on projects.

I am looking for a resource that can provide a practical basis to the theoretical Deep Learning by Goodfellow et al. I stress that the resource should be project-based, as I learn best by creating.

Do you have any recommendations?

Thank you!

2 comments

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strangecasts
Keras' code examples - https://keras.io/examples/ - tend to be structured divided into dataset-preprocessing-training, and tend to start with a somewhat underparameterized model to show off the method quickly, rather than attaining the best performance. Keras 3 is also set up to be backend-independent, so you should be able to borrow the examples' preprocessing regardless of whether you're using PyTorch, TensorFlow or Jax.

In particular, the monocular depth estimation example seems like a good start: https://keras.io/examples/vision/depth_estimation/