Neural Networks and Learning Concepts

What is the primary function of a neural network?

• To play video games

• To create art

• To learn and solve problems

• To store information

What algorithm do neural networks use to adjust weights after making a mistake?

• Linear regression

• Backpropagation

• Neural optimization

• Data fitting

What does “optimization” refer to in the context of neural networks?

• The process of designing the architecture

• Finding the best weights for predictions

• Creating new algorithms

• Reducing the size of the dataset

What is a potential issue that can arise from neural networks finding coincidental relationships in data?

• Overfitting

• Underfitting

• Data accuracy

• Model complexity

How does John Green-bot begin his exploration on the metaphorical map of optimization?

• By setting the weights to zero

• By starting with random weights

• By using pre-calculated data

• By following a straight path

What is the "learning rate" in the context of neural networks?

• The speed at which data is collected

• The rate at which weights are adjusted

• The frequency of training sessions

• The time taken to calculate errors

What does the confusion matrix display?

• The number of training images

• The accuracy of each letter prediction

• The total number of epochs

• The amount of labeled data

Which of the following statements best defines Unsupervised Learning?

• Learning that requires labeled data from a teacher

• Learning that involves finding patterns on one's own

• Learning that focuses solely on numerical data

• Learning that is only applicable to animals

What is a key assumption in unsupervised clustering?

• All objects are identical

• Some objects are more similar to each other than others

• Labels are always required

• Clustering is only done in supervised learning

What does the K-means clustering algorithm primarily need to function?

• Random predictions

• A way to compare observations and calculate averages

• A large dataset with labels

• Human intervention for every step