unit 2Learning Quiz

In which type of machine learning is the data labeled with the desired output?

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Deep Learning

An email spam filter that learns to identify spam emails based on labeled examples is an application of:

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Transfer Learning

A machine learning algorithm that groups similar customer purchases into clusters for recommendation systems uses:

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Neural Networks

An AI agent playing a game and learning from its rewards and penalties is an example of:

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Evolutionary Learning

Which of the following statements is NOT true about supervised learning?

• Requires labeled data for training.

• Used for classification and regression tasks.

• Can be less efficient for large datasets.

• Often used in image recognition applications.

In an unsupervised learning scenario, the goal is to:

• Predict a specific output based on labeled data.

• Identify patterns and relationships within unlabeled data.

• Train an AI agent through rewards and penalties.

• Develop complex neural network architectures.

Clustering algorithms are commonly used in unsupervised learning for:

• Spam filtering

• Image classification

• Stock price prediction

• Grouping similar data points

Reinforcement learning is particularly useful for scenarios where:

• Large amounts of labeled data are available.

• The desired outcome is clear, but the path to achieve it is unknown.

• The data is structured and easily categorized.

• The task requires reasoning and logical deduction.

Imagine an AI playing a game and learning to win by trial and error. This is an example of:

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Natural Language Processing

Artificial neural networks are inspired by the structure and function of:

• The human brain

• Quantum computers

• Complex mathematical models

• High-speed processors