Revision of Ch-2 (Class 10)

In an unsupervised learning scenario, the goal is to:

• Predict a specific output based on labelled data.

• Identify patterns and relationships within unlabelled 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

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

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

• The human brain

• Quantum computers

• Complex mathematical models

• High-speed processors

What is the main function of Machine Learning?

• Writing code for every action

• Running programs without any data

• Learning from data and making predictions

• Randomly selecting outputs

Deep Learning is based on which of the following?

• Rule-based programming

• Human-written instructions

• Neural networks

• Simple mathematical formulas

What are features in a dataset?

• Rows of the table

• Columns of the table

• Structure of the table

• Raw data without tags

A company is training a self-driving car to recognize pedestrians, traffic lights, and road signs using images.

They increase the dataset by flipping, rotating, and changing brightness in images. What type of learning is used in self-driving cars?

• Supervised Learning

• Deep Learning

• Semi-Supervised Learning

• Unsupervised learning

Which of the following statements best describes Artificial Intelligence (AI)?

• Al is a subset of Machine Learning that focuses on data analysis.

• Al enables machines to mimic human intelligence and make decisions.

• Al refers only to robots and self-driving cars.

• Al is only used in gaming and virtual assistants.

What is the key difference between Machine Learning (ML) and Deep Learning (DL)?

• ML uses traditional programming rules, whereas DL creates its own rules.

• ML learns from data, while DL is explicitly programmed for each task.

• DL uses artificial neural networks to analyze large amounts of data, whereas ML relies on structured datasets

  and algorithms.

• There is no difference; ML and DL are the same.