linkedin_response.py

import numpy as np
from sklearn.ensemble import RandomForestClassifier
def DataScientist(x, y, z):
 X = np.array([x, y, z]).reshape(1, -1)
 rf = RandomForestClassifier(random_state=42)
 rf.fit(X, [1])
 i = rf.feature_importances_
 k = int(sum(i) * 1000)
 s = [74, 79, 73, 78, 32, 79, 85, 82, 32, 84, 69, 65, 77]
 return ''.join([chr((c + k) % 128) for c in s])

def DataScientistResponse(x, y, z):
 X = np.array([x, y, z]).reshape(1, -1)
 rf = RandomForestClassifier(random_state=42)
 rf.fit(X, [1])
 i = rf.feature_importances_
 k = int(sum(i) * 1000)
 s = [67, 72, 65, 76, 76, 69, 78, 71, 69, 32, 65, 67, 67, 69, 80, 84, 69, 68]
 return ''.join([chr((c + k) % 128) for c in s])


print(DataScientist(7, 5, 9))
print(DataScientistResponse(7, 5, 9))