Machine Learning MIT ADT

What is machine learning?

• A technique to teach machines to think like humans

• A technique to automate repetitive tasks

• A technique to allow machines to learn from data and improve their performance

Which of the following is not a type of machine learning?

• Supervised learning

• Unsupervised learning

• Reinforcement learning

• Logical learning

Which of the following is an example of supervised learning?

• Predicting whether an email is spam or not

• Clustering a dataset into distinct groups

• Discovering hidden patterns in a dataset

• None of the above

Which of the following is an example of unsupervised learning?

• Predicting stock prices

• Recognizing handwritten digits

• Grouping similar customers based on their purchasing behavior

• None of the above

Which of the following is an example of a classification problem?

• Predicting the price of a house

• Predicting the age of a person

• Predicting whether a customer will buy a product or not

• Predicting the weight of a dog

Which of the following is an example of a regression problem?

• Classifying images into categories

• Predicting the probability of a customer clicking on an ad

• Predicting the temperature for tomorrow

• None of the above

Which of the following is not a machine learning algorithm?

• K-means clustering

• Linear regression

• Random forest

• All of the above are machine learning algorithms

Which of the following is used to evaluate the performance of a machine learning model?

• Precision and recall

• Accuracy

• F1 score

• All of the above

Which of the following is used to prevent overfitting in a machine learning model?

• Regularization

• Early stopping

• Cross-validation

• All of the above

Which of the following is not a step in the machine learning workflow?

• Data cleaning

• Feature engineering

• Model deployment

• None of the above