daviddoji/CalculusWithJuliaNotes.jl
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quarto/derivatives/numeric_derivatives.qmd
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@@ -195,11 +195,10 @@ We pass in the function object, `k''`, and not the evaluated function.
## Recap on derivatives in Julia
A quick summary for finding derivatives in `Julia`, as there are $3$ different manners:
A quick summary of the $3$ different ways for finding derivatives in `Julia` presented in these notes:
* Symbolic derivatives are found using `diff` from `SymPy`
* Automatic derivatives are found using the notation `f'` using `ForwardDiff.derivative`
* Automatic derivatives are found using the notation `f'` which utilizes `ForwardDiff.derivative`
* approximate derivatives at a point, `c`, for a given `h` are found with `(f(c+h)-f(c))/h`.