⁉️ Interview question
How does `scipy.optimize.minimize()` choose between different optimization algorithms, and what happens if the initial guess is far from the minimum?
`scipy.optimize.minimize()` selects an algorithm based on the `method` parameter (e.g., 'BFGS', 'Nelder-Mead', 'COBYLA'), each suited for specific problem types. If the initial guess is far from the true minimum, some methods may converge slowly or get stuck in local minima, especially for non-convex functions. The function also allows passing bounds and constraints to guide the search, but poor initialization can lead to suboptimal results or failure to converge, particularly when using gradient-based methods without proper scaling or preprocessing of input data.
#️⃣ tags: #scipy #python #optimization #scientificcomputing #numericalanalysis #machinelearning #codingchallenge #beginner
By: @DataScienceQ 🚀
How does `scipy.optimize.minimize()` choose between different optimization algorithms, and what happens if the initial guess is far from the minimum?
#️⃣ tags: #scipy #python #optimization #scientificcomputing #numericalanalysis #machinelearning #codingchallenge #beginner
By: @DataScienceQ 🚀
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