How can I optimize my function using NumPy?

How can I optimize my function using NumPy?

You can use the numpy library along with optimization functions from scipy.optimize. What kind of function are you trying to optimize?

I'm trying to minimize a quadratic function. Can you show me an example?

Sure! You can use scipy.optimize.minimize for that. Here's a simple example:

import numpy as np
from scipy.optimize import minimize

# Define the quadratic function
def func(x):
    return (x - 3)**2 + 2

# Initial guess
x0 = 0

# Perform optimization
result = minimize(func, x0)
print(result)

What if I have constraints on my optimization problem?

You can specify constraints using the constraints parameter in the minimize function. Would you like to see an example with constraints?