Project STEM AI Quiz

What does AI stand for?

• Artificial Intelligence

• Advanced Intelligence

• Automated Intelligence

• Algorithmic Intelligence

What is the goal of AI?

• To replace human intelligence with machines.

• To create robots that can think and feel like humans.

• To develop computer systems that can perform tasks without any human intervention.

• To develop computer systems that can perform tasks that would normally require human intelligence.

What are the two main types of AI?

• artificial intelligence and machine learning

• strong AI and weak AI

• narrow AI and general AI

• supervised learning and unsupervised learning

What is the difference between narrow AI and general AI?

• Narrow AI is designed for specific tasks, while general AI can perform any intellectual task.

• Narrow AI can only perform simple tasks, while general AI can perform complex tasks.

• Narrow AI is less intelligent than general AI.

• Narrow AI is limited to a specific domain, while general AI can learn and adapt to any domain.

What is machine learning?

• Machine learning is a technique used to analyze data and make predictions based on patterns.

• Machine learning is a field of study that focuses on developing algorithms and models that enable computers to learn and make predictions or decisions without being explicitly programmed.

• Machine learning is a process of training computers to perform tasks without human intervention.

• Machine learning is a type of software that can think and learn like a human.

What are the three main types of machine learning?

• classification learning, clustering learning, and regression learning.

• decision tree learning, random forest learning, and support vector machine learning.

• supervised learning, unsupervised learning, and reinforcement learning

• deep learning, semi-supervised learning, and transfer learning.

What is supervised learning?

• Supervised learning is a type of machine learning where an algorithm learns from unlabeled training data to make predictions or decisions.

• Supervised learning is a type of machine learning where an algorithm learns from both labeled and unlabeled training data to make predictions or decisions.

• Supervised learning is a type of machine learning where an algorithm learns from unstructured data to make predictions or decisions.

• Supervised learning is a type of machine learning where an algorithm learns from labeled training data to make predictions or decisions.

What is unsupervised learning?

• Unsupervised learning is a type of machine learning where the algorithm learns patterns and relationships in data without any labeled examples or guidance from a human.

• Unsupervised learning is a type of machine learning where the algorithm requires constant guidance from a human.

• Unsupervised learning is a type of machine learning where the algorithm learns from labeled examples.

• Unsupervised learning is a type of machine learning where the algorithm only learns patterns in labeled data.

What is reinforcement learning?

• A type of machine learning where an agent learns to make decisions by interacting with an environment and receiving feedback in the form of rewards or punishments.

• A type of machine learning where an agent learns to make decisions by randomly selecting actions.

• A type of machine learning where an agent learns to make decisions based on pre-defined rules.

• A type of machine learning where an agent learns to make decisions by analyzing large datasets.

What is the training data used for in machine learning?

• To teach a model how to make predictions or perform a task.

• To validate the model's predictions.

• To test the accuracy of the model.

• To evaluate the performance of the model.