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1. What is Machine learning?

• a) The selective acquisition of knowledge through the use of computer programs

• b) The selective acquisition of knowledge through the use of manual programs

• c) The autonomous acquisition of knowledge through the use of computer programs

• d) The autonomous acquisition of knowledge through the use of manual programs

2. K-Nearest Neighbors (KNN) is classified as what type of machine learning algorithm?

• a) Instance-based learning

• b) Parametric learning

• c) Non-parametric learning

• d) Model-based learning

3. Which algorithm is best suited for a binary classification problem?

• a) K-nearest Neighbors

• b) Decision Trees

• c) Random Forest

• d) Linear Regression

4. Which type of machine learning algorithm falls under the category of “unsupervised

learning”?

• a) Linear Regression

• b) K-means Clustering

• c) Decision Trees

• d) Random Forest

5. An artificially intelligent car decreases its speed based on its distance from the

car in front of it. Which algorithm is used?

• a) Naïve-Bayes

• b) Decision Tree

• c) Linear Regression

• d) Logistic Regression

6. Decision tree uses the inductive learning machine learning approach.

• a) False

• b) True

7. ML is a field of AI consisting of learning algorithms that?

• A. Improve their performance

• B. At executing some task

• C. Over time with experience

• D. All of the above

8. Different learning methods does not include?

• A. Introduction

• B. Analogy

• C. Deduction

• D. Memorization

9. Which of the following are ML methods?

• A. based on human supervision

• B. supervised Learning

• C. semi-reinforcement Learning

• D. All of the above

10.  Which of the following is a disadvantage of decision trees?

• A. Factor analysis

• B. Decision trees are robust to outliers

• C. Decision trees are prone to be overfit

• D. None of the above