
AI and Machine Learning
Quiz
•
Computers
•
12th Grade
•
Practice Problem
•
Hard
Dias Pramudita
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary goal of machine learning?
To cook dinner
To write poetry
To develop algorithms that can learn from data and make predictions or decisions
To build a spaceship
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are the three main types of machine learning?
supervised learning, unsupervised learning, reinforcement learning
semi-supervised learning
deep learning
cluster learning
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Explain the difference between supervised and unsupervised learning.
In supervised learning, the model learns from labeled data, while in unsupervised learning, the model learns from unlabeled data.
Supervised learning requires human intervention, while unsupervised learning is fully automated.
In supervised learning, the model learns from unlabeled data, while in unsupervised learning, the model learns from labeled data.
Unsupervised learning is more accurate than supervised learning.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is overfitting in machine learning?
Overfitting in machine learning is when a model learns the details and noise in the training data to the extent that it negatively impacts the model's performance on new data.
Overfitting is beneficial for the model's performance
Overfitting occurs when a model performs well on new data
Overfitting is when a model learns only the general patterns in the training data
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of neural networks in machine learning?
Neural networks are not effective in handling unstructured data in machine learning.
Neural networks are only used for image recognition in machine learning.
Neural networks play a crucial role in machine learning by enabling the learning of intricate patterns and relationships in data, leading to more accurate predictions and decision-making.
Neural networks are primarily used for linear regression tasks in machine learning.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does reinforcement learning work in the context of AI?
Reinforcement learning works by having an agent learn to make decisions through trial and error, receiving rewards or penalties based on its actions.
Reinforcement learning is based on unsupervised learning techniques
Reinforcement learning does not involve rewards or penalties
Reinforcement learning involves only one step decision-making
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the importance of feature selection in machine learning?
Feature selection is crucial for improving model performance, reducing overfitting, simplifying models, and enhancing interpretability.
Feature selection increases overfitting
Feature selection has no impact on model performance
Feature selection makes models more complex
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