ML WORKSHOP II CSE H

ML WORKSHOP II CSE H

University

27 Qs

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ML WORKSHOP II CSE H

ML WORKSHOP II CSE H

Assessment

Quiz

Computers

University

Hard

Created by

SUMITHA K

Used 3+ times

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27 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

Among the following option identify the one which is not a type of learning
Semi Unsupervised Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning

Answer explanation

Semi Unsupervised Learning

2.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

Identify the kind of learning algorithm for  “facial identities for facial expressions”.
Prediction
Recognition Patterns
Recognizing Anomalies
Generating Patterns

Answer explanation

For facial identities and facial expression, “recognition patterns” is used.

3.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

Identify the type of learning in which labeled training data is used.
Semi unsupervised learning
Supervised learning
Reinforcement learning
Unsupervised learning

Answer explanation

Supervised learning uses labeled training data.

4.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

Machine learning is a subset of which of the following.
Artificial Intelligence
Deep Learning
Data Learning
None of these

Answer explanation

Machine Learning is a subset of Artificial Intelligence

5.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

Application of machine learning is
email filtering
facial recognition
sentiment analysis
All of the above

Answer explanation

All of the above

6.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

K-Nearest Neighbors (KNN) is classified as what type of machine learning algorithm?
Instance-based learning
Parametric learning
Non-parametric learning
Model-based learning

Answer explanation

KNN doesn’t build a parametric model of the data. Instead, it directly classifies new data points based on the k nearest points in the training data.

7.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

Which of the following is not a supervised machine learning algorithm?
K-means
Naïve Bayes
SVM for classification problems
Decision tree

Answer explanation

Decision tree, SVM (Support vector machines) for classification problems and Naïve Bayes are the examples of supervised machine learning algorithm. K-means is an example of unsupervised machine learning algorithm.

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