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Built-in utilities for parameter fitting #86

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kach opened this issue Jan 31, 2025 · 1 comment

Owner

kach commented Jan 31, 2025

We already have examples/recipes, but it could be even easier for people if there were built-in utilities:

@memo
def f(alpha, beta): ...

f.grid_search(
  loss=lambda pred: …,
  grid=(np.linspace(…), np.linspace(…), …)
)

f.gradient_fit(
  loss=lambda pred: …,
  init=(0, 0.5),
  step_size=…,
  num_iterations=…
)

Owner Author

kach commented Feb 13, 2025

More thoughts: could use type hints on params to specify ranges. Could also automatically generate Jupyter widgets for interaction.

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