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WorksheetsModelling in AI
Total questions: 54
Worksheet time: 37mins
What is an artificial neural network?
A programming language used for web development.
A type of computer virus.
A method for organizing files on a computer.
A computational model inspired by the structure and function of biological neural networks in the brain.
What are the main components of an artificial neural network?
neurons, connections, and layers
nodes, edges, and activation functions
inputs, outputs, and thresholds
weights, biases, and activation functions
What are the different types of artificial neural networks?
deep neural networks
feedforward neural networks, recurrent neural networks, convolutional neural networks, and self-organizing maps
supervised neural networks
unsupervised neural networks
What is supervised learning in artificial neural networks?
Supervised learning is a type of machine learning where the model is trained using unlabeled data.
Supervised learning is a type of machine learning where the model does not require any training.
Supervised learning is a type of machine learning where the model is trained using reinforcement learning techniques.
Supervised learning is a type of machine learning where the model is trained using labeled data.
What is unsupervised learning in artificial neural networks?
Unsupervised learning is a type of machine learning where the model requires a large amount of labeled data to train effectively.
Unsupervised learning is a type of machine learning where the model learns from labeled examples and guidance from a supervisor.
Unsupervised learning is a type of machine learning where the model learns patterns and relationships in the data without any labeled examples or guidance from a supervisor.
Unsupervised learning is a type of machine learning where the model only learns patterns and relationships in the data without making any predictions.
What is reinforcement learning in artificial neural networks?
A type of machine learning where an agent learns to make decisions based on pre-defined rules.
A type of machine learning where an agent learns to make decisions by analyzing large datasets.
A type of machine learning where an agent learns to make decisions by interacting with an environment and receiving feedback in the form of rewards or punishments.
A type of machine learning where an agent learns to make decisions by randomly selecting actions.
What are the applications of artificial neural networks in image recognition?
Weather forecasting, stock market prediction, and language translation
Facial recognition, object detection, image segmentation, and image classification
Handwriting recognition, voice synthesis, and spam detection
Speech recognition, text generation, and sentiment analysis
How are artificial neural networks used in natural language processing?
Artificial neural networks are used to process and analyze language data in natural language processing.
Artificial neural networks are used to translate language data in natural language processing.
Artificial neural networks are used to generate language data in natural language processing.
Artificial neural networks are not used in natural language processing.
What are the applications of artificial neural networks in finance?
Supply chain management, customer relationship management, and human resources management
Weather forecasting, healthcare diagnosis, and social media sentiment analysis
Stock market prediction, credit risk assessment, fraud detection, algorithmic trading, and portfolio optimization
Image recognition, natural language processing, and autonomous vehicles
How are artificial neural networks used in medical diagnosis?
By using a magic algorithm that predicts the diagnosis.
By randomly guessing the diagnosis based on patient data.
By consulting a psychic to determine the diagnosis.
By analyzing patient data and identifying patterns and correlations.
What are the applications of artificial neural networks in robotics?
Perception, motion planning, control, and learning
Financial analysis, marketing research, and customer service
Data storage, software development, and computer networking
Speech recognition, image processing, and natural language understanding
How are artificial neural networks used in recommendation systems?
By randomly selecting items to recommend.
By analyzing market trends to make recommendations.
By using a rule-based system to generate recommendations.
By analyzing user preferences and behavior to make personalized recommendations.
What are the applications of artificial neural networks in weather prediction?
Artificial neural networks are used to analyze data and forecast weather parameters such as temperature, precipitation, and wind speed.
Artificial neural networks are used to analyze data and forecast the stock market.
Artificial neural networks are used to predict the outcome of sports events.
Artificial neural networks are used to predict the occurrence of earthquakes.
How are artificial neural networks used in fraud detection?
Artificial neural networks analyze data and identify patterns and anomalies to detect fraudulent activity.
Artificial neural networks use machine learning algorithms to detect fraudulent activity.
Artificial neural networks rely on human input to identify patterns and anomalies in data.
Artificial neural networks are not effective in fraud detection and are rarely used.
What are the applications of artificial neural networks in gaming?
Artificial neural networks have no applications in gaming.
Artificial neural networks are primarily used in gaming for graphics rendering.
Artificial neural networks are only used in gaming for character behavior and movement.
Artificial neural networks are used in gaming for various applications such as character behavior and movement, game balancing, opponent AI, procedural content generation, and player modeling.
What is Machine Learning? (Choose 3 Answers)
Artificial Intelligence
Machine Learning
Data Statistics
Deep Learning
from the picture, what kind of programming is it?
Traditional Programming
Machine Learning
Modern Programming
Traditional Learning
What kind of learning algorithm for "Future stock prices or currency exchange rates"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
Which of the following is not type of learning?
Semi-unsupervised Learning
Unsupervised Learning
Supervised Learning
Reinforcement Learning
Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
This picture shows a result of ...
Supervised Learning: Classification
Unsupervised Learning: Regression
Unsupervised Learning: Prediction
Supervised Learning: Regression
__________________ algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed.
Artificial Intelligence
Machine Learning
Deep Learning
Traditional Learning
What device below is not an example of Machine Learning?
Wearable fitness tracker
Google Assistant
Speech to Text
Google Search
None of the above
What are the three types of Machine Learning? Choose three.
Supervised Learning
Learning Differentiated
Unsupervised Learning
Reinforcement Learning
Technical Learning
What are the two types of Supervised Learning?
Classification
Declassification
Progression
Regression
What are the two types of Unsupervised Learning?
Loitering
Clustering
Association
Dissociation
In this type of Machine Learning, an AI system is presented with unlabeled, uncategorized data and the system’s algorithms act on the data without prior training. The output is dependent upon the coded algorithms.
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Technique Learning
What type of machine learning algorithm makes predictions when you have a set of input data and you know the possible responses?
Unsupervised
Reinforcement
Supervised
Deep Learning
What kind of learning algorithm for "Facial identities or facial expressions"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
ML is a field of AI consisting of learning algorithms that?
Improve their performance
At executing some task
Over time with experience
All of the above
Suppose your email program watches which emails you do or do not mark as spam, and based on that learns how to better filter spam. What is the task T in this setting?
Classifying emails as spam or not spam
Watching you label emails as spam or not spam
The number of emails correctly classified as spam/not spam
None of the above
Labeled Data are used in _______ Machine Learning algorithm
Supervised
Unsupervised
Unlabeled Data are used in _______ Machine Learning algorithm
Supervised
Unsupervised
Machine learning is mostly used when
Human expertise doesn't exist
Model must be customised to personal need
Model use huge amount of data
Interpreting the insight from descriptive data such as mean, median etc
Google Translate uses ________________ to improve its results.
Machine Learning
Internet
Machine Optimization
Data Warehouses
What is Machine Learning? (Choose 3 Answers)
Artificial Intelligence
Machine Learning
Data Statistics
Deep Learning
from the picture, what kind of programming is it?
Traditional Programming
Machine Learning
Modern Programming
Traditional Learning
Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
This picture shows a result of ...
Supervised Learning: Classification
Unsupervised Learning: Regression
Unsupervised Learning: Prediction
Supervised Learning: Regression
__________________ algorithms enable the computers to learn from data, and even improve themselves, without being explicitly programmed.
Artificial Intelligence
Machine Learning
Deep Learning
Traditional Learning
What device below is not an example of Machine Learning?
Wearable fitness tracker
Google Assistant
Speech to Text
Google Search
None of the above
What are the three types of Machine Learning? Choose three.
Supervised Learning
Learning Differentiated
Unsupervised Learning
Reinforcement Learning
Technical Learning
What are the two types of Supervised Learning?
Classification
Declassification
Progression
Regression
What are the two types of Unsupervised Learning?
Loitering
Clustering
Association
Dissociation
In this type of Machine Learning, an AI system is presented with unlabeled, uncategorized data and the system’s algorithms act on the data without prior training. The output is dependent upon the coded algorithms.
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Technique Learning
What type of machine learning algorithm makes predictions when you have a set of input data and you know the possible responses?
Unsupervised
Reinforcement
Supervised
Deep Learning
ML is a field of AI consisting of learning algorithms that?
Improve their performance
At executing some task
Over time with experience
All of the above
Suppose your email program watches which emails you do or do not mark as spam, and based on that learns how to better filter spam. What is the task T in this setting?
Classifying emails as spam or not spam
Watching you label emails as spam or not spam
The number of emails correctly classified as spam/not spam
None of the above
Labeled Data are used in _______ Machine Learning algorithm
Supervised
Unsupervised
Unlabeled Data are used in _______ Machine Learning algorithm
Supervised
Unsupervised
Machine learning is mostly used when
Human expertise doesn't exist
Model must be customised to personal need
Model use huge amount of data
Interpreting the insight from descriptive data such as mean, median etc
