
Machine Learning Quiz

Quiz
•
Computers
•
University
•
Hard

sathish kumar
FREE Resource
10 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
2 mins • 1 pt
What is Machine learning?
The selective acquisition of knowledge through the use of computer programs
The selective acquisition of knowledge through the use of manual programs
The autonomous acquisition of knowledge through the use of computer programs
The autonomous acquisition of knowledge through the use of manual programs
2.
MULTIPLE CHOICE QUESTION
30 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
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is not a supervised machine learning algorithm?
K-means
Naïve Bayes
SVM for classification problems
Decision tree
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What’s the key benefit of using deep learning for tasks like recognizing images?
They need less training data than other methods.
They’re easier to explain and understand than other models.
They can learn complex details from the data on their own.
They work faster and are more efficient computationally.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which algorithm is best suited for a binary classification problem?
K-nearest Neighbors
Decision Trees
Random Forest
Linear Regression
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the key difference between supervised and unsupervised learning?
Supervised learning requires labeled data, while unsupervised learning does not.
Supervised learning predicts labels, while unsupervised learning discovers patterns.
Supervised learning is used for classification, while unsupervised learning is used for regression.
Supervised learning is always more accurate than unsupervised learning.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which type of machine learning algorithm falls under the category of “unsupervised learning”?
Linear Regression
K-means Clustering
Decision Trees
Random Forest
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