Machine Learning & AI Quiz

What is Machine Learning?

• A subset of AI that enables computers to learn from data

• A method of manually programming computers

• A replacement for human intelligence

• A process where machines function without any data

What is the key difference between labelled and unlabelled data?

• Labelled data has predefined outputs, unlabelled data does not

• Unlabelled data is more accurate

• Labelled data is used only for supervised learning

• Labelled data is only used in deep learning

In supervised learning, what is provided to the algorithm?

• Only input data

• Input data along with corresponding output labels

• Randomly generated data without labels

• Predefined machine instructions

Which of the following is an example of unsupervised learning?

• Classifying emails as spam or non-spam

• Predicting house prices

• Grouping customers based on purchasing behavior

• Detecting fraudulent transactions

Why is reinforcement learning needed?

• It allows machines to learn through trial and error

• It only works with labelled data

• It follows a predefined set of rules

• It does not require feedback from the environment

Which of the following is a real-world application of reinforcement learning?

• Customer segmentation

• Stock market trend prediction

• Training autonomous robots

• Image recognition

In which industry is AI commonly used for fraud detection?

• Healthcare

• Finance

• Agriculture

• Manufacturing

How is AI applied in healthcare?

• By performing automated medical diagnoses

• By replacing human doctors entirely

• By increasing hospital bills through automation

• By predicting weather patterns

How do artificial neural networks (ANNs) help in machine learning?

• By mimicking the human brain’s structure and learning patterns

• By replacing all traditional computing methods

• By only processing text data

• By eliminating the need for large datasets

What is a key feature of deep learning compared to traditional machine learning?

• It requires minimal computing power

• It uses multiple layers of neural networks

• It does not require any labelled data

• It is only used for supervised learning