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Machine Learning Overview

Total questions: 11

Worksheet time: 9mins

Name
Class
Date
1.

Applications of Machine Learning (Select all that apply).

a)

Image processing

b)

Speech recognition

c)

Predicting weather

d)

Surfing on website

2.

      A program is said to learn from its _____(E) with respect to some ____(T) and _____ measure(P), if its P at T improves with E.

What is E, T and P?

a)

Experience, Target, Performance

b)

Explaination, Target, Performance

c)

Experience, Task, Performance

d)

Explaination, Task, Poll

3.

"A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E."

Suppose your email program watches which emails you do or do not mark as spam, and based on that learns how to better filter spam. What is the task T in this setting?

a)

Classify emails as spam or not spam.

b)

Watching you label emails as spam or not spam.

c)

The number (or fraction) of emails correctly classified as spam/not spam.

d)

None of the above, this is not a machine learning algorithm.

4.

What type of ML algorithm will you choose when you have set of input data and you know the possible responses?

a)

Supervised learning

b)

Unsupervised learning

c)

Deep learning

d)

Neural network

5.

ML is sub-set of AI. True or false.

a)

True

b)

False

6.

What category of machine learning algorithm finds patterns in the data when the data is not labeled?

a)

Supervised learning

b)

Unsupervised learning

c)

Data Prophecy

d)

Reinforcement learning

7.

    Predicting housing prices in coming 2 years based on area per sq.km and last 5 years prices.

Identify above suits for which algorithm?

a)

Linear regression

b)

Decision tree

c)

K-Means

d)

Support vector Machine

8.

Identify dependent variable in above problem.

a)

Typing speed

b)

Weeks of practice

c)

Words per minute

9.

      Which of the following is true about reinforcement learning?

a)

The agent gets rewards or penalty according to the action

b)

It’s an online learning

c)

The target of an agent is to maximize the rewards

d)

All of the above

10.

In self driven automated car, what is an agent and environment?

a)

agent: Other vehicles

environment: road

b)

agent: Car

environment: passengers sitting in a car

c)

agent: Car

environment: road and surrounding vehicles

d)

agent: passengers sitting in a car

environment: road and surrounding vehicles

11.

____occurs when our machine learning model is not able to capture the underlying trend of the data and performs poorly over test and train set.

a)

Overfitting

b)

Underfitting