Artificial Intelligence and Machine Learning Fundamentals Flashcards

Which of the following best describes machine learning?

Answer: A subset of AI where systems learn patterns from data without being explicitly programmed

Machine learning is a subset of AI in which algorithms learn from data to improve performance on tasks without being explicitly programmed for each scenario.

In a supervised learning model, what is the role of labeled training data?

Answer: It provides input-output pairs so the model can learn the mapping between them

Labeled training data pairs inputs with correct outputs, allowing the supervised learning algorithm to learn the relationship and generalize to new examples.

What is the primary purpose of a neural network's activation function?

Answer: To introduce non-linearity so the network can learn complex patterns

Activation functions introduce non-linearity into neural networks, enabling them to learn and represent complex, non-linear relationships in data.

Which machine learning approach is best suited for training an agent to play a video game by rewarding good moves?

Answer: Reinforcement learning

Reinforcement learning trains agents by providing rewards for desired actions and penalties for undesired ones, making it ideal for game-playing AI.

What does 'overfitting' mean in the context of machine learning?

Answer: The model learns the training data too well, including noise, and fails to generalize

Overfitting occurs when a model memorizes training data noise and specifics, resulting in high training accuracy but poor performance on unseen data.

Which of the following is an example of unsupervised learning?

Answer: Customer segmentation grouping similar buyers without predefined categories

Unsupervised learning finds hidden patterns or groupings in data without labeled outputs; customer segmentation is a classic clustering example.

In the CodeHS AI curriculum, what is a 'training set' used for?

Answer: Teaching the model by exposing it to examples so it can learn patterns

The training set is the data used to fit or teach the model, allowing it to learn the patterns needed to make predictions.