ML-1

ML-1

Professional Development

12 Qs

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Assessment

Quiz

Professional Development

Professional Development

Hard

Created by

viji parthasarathy

Used 46+ times

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12 questions

Show all answers

1.

MULTIPLE SELECT QUESTION

20 sec • 2 pts

1) What is machine learning?

    Machine learning is the science of getting computers to act without being explicitly programmed.

             Machine Learning is a form of AI that enables a system to learn from Data.

Both A and B.

None of the above.

Answer explanation

Media Image

2.

MULTIPLE CHOICE QUESTION

20 sec • 2 pts

1) Machine learning is an application of  ___________.

  Block chain.

Artificial Intelligence.

c)    Both A and B.

None of the above

Answer explanation

Media Image

3.

MULTIPLE CHOICE QUESTION

20 sec • 2 pts

3) Application of Machine learning is __________.

Email filtering

Sentimental Analysis

Face Recognition

All of the above

Answer explanation

SUPER

4.

MULTIPLE CHOICE QUESTION

20 sec • 2 pts

5) Machine learning approaches can be traditionally categorized into __ categories.

4

3

5

2

5.

MULTIPLE CHOICE QUESTION

20 sec • 2 pts

7) ___ is the machine learning algorithms that can be used with labeled data.

a) 

b)

c) 

d)

Regression algorithms

Clustering algorithms

Association algorithms

All of the above

6.

MULTIPLE SELECT QUESTION

1 min • 5 pts

Suppose an online shoe store wants to create a supervised ML model that will provide personalized shoe recommendations to users. That is, the model will recommend certain pairs of shoes to Marty and different pairs of shoes to Janet. The system will use past user behavior data to generate training data. Which of the following statements are true?

"Shoes that a user adores" is a useful label.

"The user clicked on the shoe's description" is a useful label.

"Shoe size" is a useful feature.

"Shoe beauty" is a useful feature.

Answer explanation

Media Image

7.

MULTIPLE CHOICE QUESTION

20 sec • 2 pts

________ is used as an input to the machine learning model for training and prediction purposes.

    

      Feature

  Feature Vector

      A and B

      None of the above

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