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Answer:
Classification
Explanation:
Building a machine learning solution that can predict the success of a student in completing a college degree is a binary problem. There are two possible answer: success or not success.
This brings us to a supervised machine learning problem, where one trains the technique with labeled data whether it is a success or not. Since the target variable is discrete (not continuous), classification technique has to be used.
Answer:
import random
randomlist = []
for i in range(0,20):
n = random.randint(-29,30)
if n < 0 :
n = 100
randomlist.append(n)
print(randomlist)
Explanation:
The random module is first imported as it takes care of random. Number generation.
An empty list called randomliay is created to hold the generated random integers.
Using a for loop, we specify the range of random numbers we want.
Inside the for loop ; we attach our generated random integer which will be in the range (-29 to 30) in a variable n
For each n value generated, if the value is less than 0( it is negative, since all the values are integers), replace the value with 100.
Answer:
num1 = int(input("Enter value: "))
num2 = int(input("Enter value: "))
if num1 == num2:
print("Equals.")
else:
print("Unequal.")
Explanation:
