Neural Networks and Optimization Concepts

What are the two main components that make up a neural network?

• Input and Output

• Architecture and Weights

• Neurons and Connections

• Layers and Functions

What is the process called when a neural network adjusts its internal settings to reduce errors and make better predictions?

• Calculation

• Prediction

• Optimization

• Analysis

In a graph showing the number of swimmers versus temperature, what is the main goal of linear regression?

• To draw a random line on the graph

• To make the error between the line and data points as small as possible

• To predict only the highest number of swimmers

• To ignore data points that don't fit the pattern

In complex neural networks with many output neurons, what is used to represent the difference between the predicted answer and the correct answer?

• A single error number

• A loss function

• A simple calculation

• A data point

What is the main goal when training a neural network?

• To make the network as complex as possible.

• To find the best combination of weights to get the lowest error.

• To use as much training data as possible.

• To adjust the learning rate frequently.

In the jungle exploration example, what did John Greenbot find when he couldn't go down any further in his current location?

• The global optimal solution.

• The highest mountain peak.

• A local optimal solution.

• The starting point of his journey.

In the jungle exploration example, what does the "learning rate" represent?

• The total distance the explorer traveled.

• The number of explorers searching for the valley.

• How much the explorer's step size is adjusted to descend into a valley.

• The altitude of the deepest valley.

What is the danger of "overfitting" in a neural network?

• The network becomes too slow to process data.

• The network makes strange errors when given new, unseen data.

• The network cannot find any relationships in the data.

• The network requires more processing power than available.