How to calculate dot product of two vectors in Python?

To calculate the dot product of two vectors in Python, you can use the NumPy library, which provides a convenient dot() method for this purpose. Here’s an example:

import numpy as np

a = np.array([1, 2, 3])
b = np.array([4, 5, 6])

dot_product = np.dot(a, b)
print(dot_product)

In this example, we define two NumPy arrays a and b to represent our vectors. We then call the dot() method of the NumPy library to calculate the dot product of a and b and store the result in the dot_product variable. Finally, we print the value of dot_product.

The dot product of two vectors a and b is calculated as a[0]*b[0] + a[1]*b[1] + ... + a[n-1]*b[n-1].

Alternatively, if you do not want to use NumPy, you can implement the dot product calculation yourself using a list comprehension, like this:

a = [1, 2, 3]
b = [4, 5, 6]

dot_product = sum([a[i] * b[i] for i in range(len(a))])