stud
bud
Sign up
Log in
Home
Library
Explore
SAT
More
Unit 2 Grade X 25-26 Flashcards | StudBud
Explore
/
Unit 2 Grade X 25-26
Unit 2 Grade X 25-26
33 terms
·
StudBud Administration
·
77 plays
Imported from external platform
Flashcards
33 cards
F
Practice quiz
P
Host live
L
Questions
33
Answers
1
. Which of the following applications use Deep Learning?
Handwritten digit recognition
Email writing
Basic calculators
Google search suggestions
2
. A classification model predicts continuous numerical values.
False
True
3
Unsupervised learning is commonly used for fraud detection and anomaly detection.
True
False
4
Deep Learning models like Convolutional Neural Networks (CNNs) are best suited for image recognition tasks.
False
True
5
Reinforcement learning is particularly useful for scenarios where:
The task requires reasoning and logical deduction.
The desired outcome is clear, but the path to achieve it is unknown.
Large amounts of labeled data are available.
The data is structured and easily categorized.
6
10. Artificial neural networks are inspired by the structure and function of:
b) Quantum computers
d) High-speed processors
c) Complex mathematical models
a) The human brain
7
Artificial Intelligence (AI) is a subset of Machine Learning (ML).
True
False
8
. A rule-based Al model adapts and learns from new data without human intervention.
False
True
9
Supervised learning models require labelled data for training.
False
True
10
Which of the following requires the largest amount of data ?
Machine Learning
Deep Learning
None of the above
Al
11
1 Deep Learning is based on which of the following?
Rule-based programming
Human-written instructions
Simple mathematical formulas
Neural networks
12
A neural network with multiple layers of interconnected neurons is called a: a
b) Deep Neural Network
d) Perceptron
c) Linear network
a) Single-layer network
13
In an unsupervised learning model, the system learns from labelled data.
True
False
14
Artificial Neural Networks (ANNs) are designed to mimic the way the human brain processes information.
True
False
15
What is a dataset?
(a)A machine learning model
None of the above
Machine Learning
A collection of organized data
16
. Imagine an AI playing a game and learning to win by trial and error. This is an example of:
Natural Language Processing
Reinforcement Learning
Supervised Learning
Unsupervised Learning
17
In an unsupervised learning scenario, the goal is to:
Identify patterns and relationships within unlabeled data.
Develop complex neural network architectures.
) Predict a specific output based on labeled data.
) Train an AI agent through rewards and penalties.
18
1. In which type of machine learning is the data labeled with the desired output?
d) Deep Learning
b) Unsupervised Learning
a) Supervised Learning
c) Reinforcement Learning
19
. What is an example of data preprocessing?
) Collecting more data
) Ignoring incorrect data
Training the model without cleaning the data
A spreadsheet with rows and columns
20
A machine learning algorithm that groups similar customer purchases into clusters for recommendation systems uses:
Unsupervised Learning
Reinforcement Learning
Neural Networks
Supervised Learning
21
Which of the following statements is NOT true about supervised learning?
Requires labeled data for training.
) Can be less efficient for large datasets.
Often used in image recognition applications.
Used for classification and regression tasks.
22
. An email spam filter that learns to identify spam emails based on labeled examples is an application of:
Unsupervised Learning
Reinforcement Learning
Supervised Learning
Transfer Learning
23
A regression model is used when the output is a continuous value.
False
True
24
Association models in machine learning help in finding relationships between different items in a dataset.
True
False
25
In supervised learning, the model discovers hidden patterns in data without predefined labels.
False
True
26
What is the main function of Machine Learning
Leaming from data and making predictions
Writing code for every action
Randomly selecting outputs
Running programs without any data
27
Deep Learning (DL) is a specialized field of Machine Learning that uses neural networks.
True
False
28
Neural networks are particularly well-suited for tasks involving:
a) Simple calculations and mathematical operations
b) Recognizing patterns in complex data like images and text
d) Storing and retrieving large amounts of information
c) Performing logical deductions and reasoning tasks
29
A training dataset is used to evaluate how well a machine learning model performs.
False
True
30
. Clustering algorithms are commonly used in unsupervised learning for:
Image classification
Stock price prediction
) Grouping similar data points
) Spam filtering
31
Training a neural network often requires:
A human expert to guide the learning process
a) A small set of labeled data samples
A specific set of programming instructions
A significant amount of data and computational resources
32
Reinforcement learning involves an agent learning through rewards and penalties.
False
True
33
. An AI agent playing a game and learning from its rewards and penalties is an example of:
Unsupervised Learning
Reinforcement Learning
Evolutionary Learning
Supervised Learning
