added docs for the changes

Signed-off-by: AdityaPandeyCN <[email protected]>

Author: AdityaPandeyCN

docs/src/solvers/nonlinear_least_squares_solvers.md

@@ -79,6 +79,15 @@ Submethod choices for this algorithm include:
   - `:lmdif`: Advanced Levenberg-Marquardt
   - `:hybrd`: Advanced modified version of Powell's algorithm
 
+### SciPy (Python via PythonCall)
+
+A wrapper over `scipy.optimize.least_squares`.  Requires that the Python
+package `scipy` is available to PythonCall.
+
+  - [`SciPyLeastSquares()`](@ref) with convenience constructors
+    `SciPyLeastSquaresTRF()`, `SciPyLeastSquaresDogbox()`, and
+    `SciPyLeastSquaresLM()` for the common method choices.
+
 ### Optimization.jl
 
 `NonlinearLeastSquaresProblem`s can be converted into an `OptimizationProblem`  and used

docs/src/solvers/nonlinear_system_solvers.md

@@ -186,3 +186,13 @@ This is a wrapper package for importing solvers from PETSc.jl into the SciML int
     [PETSc.jl](https://github.com/JuliaParallel/PETSc.jl)
 
 For a list of possible solvers see the [PETSc.jl documentation](https://petsc.org/release/manual/snes/)
+
+### SciPy (Python via PythonCall)
+
+These wrappers let you use the algorithms from
+[`scipy.optimize`](https://docs.scipy.org/doc/scipy/reference/optimize.html)
+without leaving Julia.  SciPy is loaded lazily through PythonCall, so these
+methods are available whenever the `scipy` Python package can be imported.
+
+  - [`SciPyRoot()`](@ref): wrapper for `scipy.optimize.root` (vector problems)
+  - [`SciPyRootScalar()`](@ref): wrapper for `scipy.optimize.root_scalar` (scalar/bracketed problems)