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Reflection Point_Machine Learning Techniques for Real-World

Total questions: 20

Worksheet time: 21mins

Name
Class
Date
1.

Compute the co-variance matrix

a)
b)
c)
2.

Calculate the eigen values for

a)

λ=8.22\lambda=8.22

b)

λ=7.2\lambda=7.2

c)

λ=1.2\lambda=1.2

3.

Identify which statement is not true regarding principal components?

a)

orthogonal

b)

linear combination of original variables

c)

capture the variance in the data

d)

finds the correlation

4.

PCA is technique for

a)

variance normalisation

b)

data augmentation

c)

dimensionality reduction

d)

feature extraction

5.

A measure of goodness of fit for the estimated regression equation is the

a)

mean square due to error

b)

multiple coefficient of determination

c)

mean square due to regression

6.

---------- maintains the state of the previous conversation.

a)

Intent classifier

b)

Entity extractor

c)

Dialogue Tracking

d)

Dialogue Policy

7.

Depicts ---------- model

a)

CBOW

b)

BOW

c)

Skip-Gram

8.

Saving the output of a particular layer and feeding this back to the input in order to predict the output of

the layer.

a)

Recurrent Neural Network

b)

Feed-Forward Neural Network

c)

Feed-Backward Neural Network

d)

CNN

9.

is ---------- type of RNN

a)

One to One

b)

One to Many

c)

Many to One

d)

Many to Many

10.

"If I put my hand in a fire, then it will burn" is an example of

a)

common sense reasoning

b)

Abduction Reasoning

c)

Induction Reasoning

11.

The input image has been converted into a matrix of size 28 X 28 and a kernel/filter of size 7 X 7 with a stride of 1. What will be the size of the convoluted matrix?

a)

22x22

b)

25X25

c)

21X21

d)

23X21

12.

Assume a simple MLP model with 3 neurons and inputs= 1,2,3. The weights to the input neurons are 4,5 and 6 respectively. Assume the activation function is a linear constant value of 3. What will be the output ?

a)

96

b)

124

c)

84

d)

128

13.

Which of the following is well suited for perceptual tasks?

a)

Convolutional neural networks

b)

Feed-forward neural networks

c)

Recurrent neural networks

d)

Reinforcement Learning

14.

Which neural network has only one hidden layer between the input and output?

a)

Recurrent neural networks

b)

Shallow neural network

c)

Deep neural network

d)

Feed-forward neural networks

15.

---------- compares metric values across different subgroups of the data.

a)

Bar Chart

b)

Column chart

c)

Line chart

d)

Histogram

16.

Box plot does not visualize

a)

First Quartile or 25%

b)

Median

c)

Third Quartile or 75%

d)

Mean

17.

shows the distribution of a continuous variable.

a)

histogram

b)

Scatterplot

c)

boxplot

18.

------- shows multi-collinearity in a dataset

a)

Heatmap

b)

BOX PLOT

c)

Correlation matrix

19.

---------- shows a static number and how categories represent part of a whole the composition of something.

a)

Pie-chart

b)

Bar chart

c)

Line chart

d)

Box plot

20.

shows ---- plot

a)

violin plot

b)

Box plot

c)

whisker plot

d)

scatterplot