Hello World Example

[sadamov]

Description:

We should add a HelloWorld.ipynb notebook in the docs folder to provide a step-by-step guide for users to run a full model training using DANRA data. This will improve onboarding and showcase the capabilities of neural-lam.

Proposed notebook contents:

1. Install Neural-LAM with all dependencies using PDM (+ ipykernel)
2. Data loading and preprocessing (using https://github.com/leifdenby/neural-lam/blob/0a79c74cb1d6bf3e29b999188c0c6e4d9f95078b/tests/datastore_examples/mllam/danra.example.yaml)
3. Model configuration and HiLAM graph generation with https://github.com/leifdenby/neural-lam/blob/0a79c74cb1d6bf3e29b999188c0c6e4d9f95078b/neural_lam/create_graph.py
4. Training process (using --flags) on CPU
5. Evaluation and visualization using built in maps and charts + wandb

Additional considerations:

• Use a small subset of DANRA data for quick execution
• Include explanations for each step
• Highlight key parameters and their effects
• Provide tips for scaling to larger datasets

This addition will significantly enhance the user experience and make it easier for new contributors to get started with neural-lam. Especially now that we offer multiple datastores and the README might become slightly more complex.

[joeloskarsson]

I agree that this would be great! While we could make it as a notebook, I also think such a "getting started guide" should be part of #61. More reason to put some effort into a proper documentation setup 😅