Worksheets13. SL ANN
Total questions: 16
Worksheet time: 8mins
What is the primary goal of multi-class classification in computer vision?
To classify images into two categories
To classify images into multiple categories
To enhance image quality
To reduce image size
In the one-vs-all algorithm, how is a multi-class problem typically approached?
By training a single model for all classes
By training multiple binary classifiers
By using unsupervised learning
By clustering the data
Which of the following is NOT an application of Artificial Neural Networks (ANN)?
Facial Recognition
Real-time Translation
Image Compression
Basic Arithmetic Operations
Which of the following is a key component of a biological neuron?
Dendrites
Axon
Synapse
All of the above
In the context of ANN, what does the term "activation function" refer to?
A function that initializes weights
A function that determines the output of a neuron
A function that reduces overfitting
A function that increases learning rate
Which of the following is a characteristic of supervised learning?
No labeled data is used
Labeled data is used for training
It is only applicable to classification tasks
It does not require a training set
What is the purpose of using fuzzy logic in AI?
To create binary decisions
To handle uncertainty and imprecision
To optimize algorithms
To enhance image processing
Which of the following is a common method for training neural networks?
Gradient Descent
K-Means Clustering
Decision Trees
Genetic Algorithms
What does the term "overfitting" refer to in machine learning?
A model that performs well on training data but poorly on unseen data
A model that generalizes well to new data
A model that is too simple
A model that uses too few features
Which of the following is a benefit of using artificial neural networks?
They require less data than traditional algorithms
They can model complex relationships
They are always faster than other algorithms
They do not require tuning of parameters
What is the significance of the "training set" in machine learning?
It is used to evaluate the model's performance
It is used to make predictions
It is used to train the model
It is used to visualize data
Which of the following best describes "adversarial search"?
A search method for optimization problems
A search method used in competitive environments
A search method for unsupervised learning
A search method for data retrieval
What is the main advantage of using real-time translation applications?
They require no internet connection
They provide instant communication across languages
They are always accurate
They are easy to implement
Which of the following is a key feature of deep learning?
It uses shallow networks
It requires less data than traditional machine learning
It involves multiple layers of neurons
It is only applicable to image data
What is the role of "constraint satisfaction problems" in AI?
To optimize neural networks
To solve problems with specific constraints
To classify data
To enhance image recognition
Which of the following is a common activation function used in neural networks?
Linear Function
Sigmoid Function
Quadratic Function
Exponential Function
