Chapter 1: Introduction to Machine Learning

Question 1:

What is the main difference between traditional programming and machine learning?

a) Traditional programming relies on explicit rules, while machine learning models learn patterns from data.

b) Traditional programming uses data to predict outcomes, while machine learning creates rules from predictions.

c) Machine learning can only handle small datasets, while traditional programming is better for large datasets.

d) Traditional programming is faster than machine learning for all tasks.

Question 2:

Which of the following is an example of supervised learning?

a) Clustering customers based on purchasing behavior

b) Predicting house prices based on features like location and size

c) A robot learning to walk by receiving feedback

d) Reducing the dimensions of a dataset using PCA

Question 3:

In 2024, which machine learning trend focuses on training models without requiring large amounts of labeled data?

a) Federated learning

b) Explainable AI

c) Self-supervised learning

d) Reinforcement learning

Question 4:

Which of the following tools enables distributed model training without sharing raw data between devices?

a) Transformers

b) Federated learning

c) Vision Transformers

d) Transfer learning