Machine Learning Study Jam

Question 1

What does hyperparameter tuning do?

a)Optimizes parameters to improve performance of a learning algorithm

b)Expands the parameter set of a model to improve performance

c)Specifies the hyperplane that represents linear classifiers

d)Takes parameter tuning so far that performance degrades

Question 2

What is principal component analysis?

a)A feature selection technique that adds or removes features to optimize prediction accuracy

b)A linear feature transformation technique for reducing data dimensionality

c)A clustering technique that partitions data into mutually exclusive clusters

d)A predictive technique that identifies a better set of parameters

Question 3

What activation function is it?
Responsive image

a)Sigmoid

b)Relu

c)tanh

Question 4

What activation function is it?
Responsive image

a)Sigmoid

b)Relu

c)tanh

Question 5

Which of the following is a loss function?

a)Sigmoid Function

b)Cross Entropy

c)ReLu

d)All of the above

Question 6

For a binary classification problem, which of the following activation functions is used?

a)Relu

b)Softmax

c)Sigmoid

d)Tanh

Question 7

Which of the following is not a neural network?

a)CNN

b)RNN

c)KNN

d)GAN

ML Level : Beginner

Question 1

Question 2

Question 3

Question 4

Question 5

Question 6

ML Level : Intermediate

Question 1

Question 2

Question 3

Question 4

Question 5

Question 6

ML Level : advanced

Question 1

Question 2

Question 3

Question 4

Question 5

Question 6

Question 7

Your marks : 0/0