CS21 Understanding Machine Learning Basics

What is the main idea behind machine learning as described in the text?

• Computers are programmed to perform tasks without any data.

• Computers learn to perform tasks through experience and data.

• Computers can only perform tasks they are explicitly programmed for.

• Computers use human brains to improve their tasks.

How do computers learn to differentiate between a picture of a dog and a picture of a cat?

• By memorising each picture individually.

• By identifying statistical patterns in the data.

• By being programmed with specific rules for each animal.

• By using human intuition.

What is one example of a simple yet effective algorithm mentioned in the text?

• A complex neural network.

• A decision tree.

• An optimal line separating cats from dogs.

• A random forest.

What happens as a computer receives more data?

• Its algorithm becomes less accurate.

• It requires more human intervention.

• Its algorithm becomes more finely tuned and accurate.

• It stops learning.

Which of the following is NOT an application of machine learning mentioned in the text?

• Facial recognition.

• Text to speech recognition.

• Weather forecasting.

• Credit card fraud detection.

What fields are combined in machine learning to enable computers to learn?

• Biology and chemistry.

• Physics and mathematics.

• Statistics and computer science.

• Literature and history.

What is the role of the programmer in machine learning according to the text?

• To identify patterns in the data.

• To establish the algorithm for sorting future data.

• To feed data and let the computer identify patterns.

• To manually sort each piece of data.

What is the potential of machine learning as described in the text?

• To replace all human jobs.

• To transform our world in various fields.

• To make computers self-aware.

• To eliminate the need for data.

Which university is mentioned in the text as conducting machine learning research?

• University of Cambridge.

• University of Oxford.

• Harvard University.

• Stanford University.

What is a key benefit of machine learning in terms of computing power?

• It requires more computing power over time.

• It uses less computing power to solve complex problems.

• It eliminates the need for computing power.

• It only works with maximum computing power.