I am not too happy to be a good man in my world but he is made me very very much and he is made me very very much and he is very much very good to him very much and he is very much very good to you very good and very much to be able for my kids with a little more money will not go back and you can do the greatest if he can be very much and you have no problem and then we do all the way that we are not the right answer but you have a question to do and you don’t have the right right answer the answer right back and he will not be very good I am very good and he is very very bad
B = x is equal to 5
and
C = “ have special meaning and should not be used when naming variables “.
Answer:
#HERE IS CODE IN PYTHON
#function to find length of shortest and longest string in the array
def fun(list2):
#find length of shortest string
mn=len(min(list2))
#find length of longest string
mx=len(max(list2))
#return both the value
return mn,mx
#array of strings
list2 = ['Ford', 'Volvo', 'BMW', 'MARUTI','TATA']
# call the function
mn,mx=fun(list2)
#print the result
print("shortest length is:",mn)
print("longest length is:",mx)
Explanation:
Create an array of strings.Call the function fun() with array as parameter. Here min() function will find the minimum string among all the strings of array and then len() function will find its length and assign to "mn". Similarly max() will find the largest string and then len() will find its length and assign to "mx". Function fun() will return "mn" & "mx".Then print the length of shortest and longest string.
Output:
shortest length is: 3
longest length is: 5
Answer:
a. This is an instance of overfitting.
Explanation:
In data modeling and machine learning practice, data modeling begins with model training whereby the training data is used to train and fit a prediction model. When a trained model performs well on training data and has low accuracy on the test data, then we say say the model is overfitting. This means that the model is memorizing rather Than learning and hence, model fits the data too well, hence, making the model unable to perform well on the test or validation set. A model which underfits will fail to perform well on both the training and validation set.
The answer to this question would be "Licensing"
