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Which of the following optimization methods in SciPy does not require the gradient of the function being minimized?
Nelder-Mead
BFGS
L-BFGS-B
CG
In the context of SciPy's optimization, what does the 'bounds' parameter specify in the 'minimize' function?
The maximum number of iterations allowed
The range of values for each variable
The convergence criteria
The initial guess for the variables
Which of the following methods is best suited for optimizing a convex function?
Nelder-Mead
BFGS
Powell
CG
What is the primary advantage of using the 'L-BFGS-B' method over 'BFGS'?
It can handle large-scale problems
It does not require gradient information
It allows for box constraints
It is faster for small problems
Which of the following statements about the 'minimize' function in SciPy is true?
It can only minimize scalar functions
It can minimize functions with constraints
It supports both local and global optimization
It requires the objective function to be continuous
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10 Modules