what is output :

import numpy
speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x = numpy.mean(speed) print(x)

y = numpy.median(speed) print(y)

z = stats.mode(speed) print(z)

Regression is

• Supervised

• un Supervised

• rain forsment

Logistic Regression is

• Regression

• Classification

Regression data is

• continuous data

• category data

Classification data is

• continuous data

• category data

when learning rate almost to zero

in gradient descent Equation ??

• Maximum iterations

• Minimum iterations

Machine learning models should work automatically without the need for the

user to manually set the hyperparameters.

• True

• False

While training your regression model using Gradient Decent, you noticed that the

value of loss increases with epochs, this behavior can be due to high learning

rate.

• True

• False

Cleaning Empty Cells which function we use ?

• df.dropna()

• df.fillna(130, inplace = True)

• df.loc[7, 'Duration'] = 45

• A & B

• Non of them

Removing Duplicates which function we use ?

• df.dropna()

• df.fillna(130, inplace = True)

• df.loc[7, 'Duration'] = 45

• A & B

• NON of them