Answer:
import numpy as np
def sample_median(n, P):
return np.median( np.random.choice ( np.arange (1, len(P) + 1 ), n, p = P ) )
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(5, [0.3,0.7])
print(sample_median(5, [0.3,0.7])
Explanation:
- Bring in the numpy library to use the median function provided by the numpy library.
- Define the sample_median function that takes in 2 parameters and returns the median with the help of built-in random, choice and arrange functions.
- Call the sample_median function by providing some values to test and then display the results.
Output:
4.5
4.0
2.0
1.0
Answer:
Succeed and show traction within 6-10 months.
Explanation:
Ai (Artificial Inteliigence), also known as machine intelligence, is a branch of computer science that is specialized in making smart machines that are capable of doing human tasks
AI Transformation Playbook is a guide to use AI in enterprises successfully, written by Co-founder of Google Brain, Andrew Ng. In his guide, he unveiled the steps that can be followed to successfully installing AI in enterprises, companies, etc.
The most important trait of the first pilot projects is that it succeeds and begins to show traction within 6-10 months.
In his guide, he summarised five steps to install AI in enterprises. The first step is to 'Execute pilot projects to gain momentum.'
The most important trait of beginning with AI projects is that it succeeds first before being most valuable projects. The success is important as it will help to achieve familiarity and will help other people of the company to invest in this project more.
This success begins to show tractions within 6-12 months of its success.
<span>Net speed can be calculated by deducting errors in gross wpm which is more accurate </span>