AML Supervised & Unsupervised Learning Algorithms

Question 1

What distinguishes supervised learning from unsupervised learning?

Accepted Answer

Supervised learning uses labeled data, unsupervised does not

Answer

Supervised learning uses unlabeled data.

Answer

Unsupervised learning uses labeled data.

Answer

They are both identical in data handling.

Question 2

Which algorithm is commonly used in supervised learning?

Accepted Answer

Linear Regression

Answer

K-Means Clustering

Answer

PCA

Answer

Autoencoders

Question 3

What is a common use case for unsupervised learning?

Accepted Answer

Customer segmentation

Answer

Spam detection

Answer

Sentiment analysis

Answer

Credit scoring

Question 4

Which of these is an unsupervised learning technique?

Accepted Answer

K-Means Clustering

Answer

Decision Trees

Answer

Support Vector Machines

Answer

Random Forest

Question 5

Which metric is typically used to evaluate classification algorithms?

Accepted Answer

Accuracy

Answer

Mean Squared Error

Answer

Silhouette Score

Answer

R-squared

Question 6

What does dimensionality reduction do in machine learning?

Accepted Answer

Reduces input variables while retaining important data

Answer

Increases dataset complexity

Answer

Removes all features from the dataset

Answer

Adds new synthetic features

Question 7

Which technique is used to evaluate a supervised model’s performance?

Accepted Answer

Cross-validation

Answer

Feature selection

Answer

Hyperparameter tuning

Answer

Normalization

Question 8

What is the goal of clustering in unsupervised learning?

Accepted Answer

Grouping similar data points

Answer

Classifying known labels

Answer

Minimizing data quality

Answer

Encoding categorical variables

Question 9

Which algorithm is NOT used for classification tasks?

Accepted Answer

K-Means Clustering

Answer

Logistic Regression

Answer

Naive Bayes

Answer

Decision Tree