• Introduction to Machine Learning

Ture and False

1. Deep Learning is part of machine learning, in which we use artificial neural networks models.

2. Artificial intelligence is a subfield of machine learning.

3. A categorical attribute assumes values that are integer or real.

4. A dataset is a collection of data examples and their attributes.

5. An unsupervised learning algorithm learns from a training dataset with both input attributes and output levels.

6. The machine learning stages are training and testing.

Choose exactly ONE answer for each of the following questions.

7.The output attributes of classification are:
(a)categorical values
(b)numeric values
(c)categorical or numeric values
(d)categorical and numeric values

8.Three types of machine learning are:
(a)deep learning, moderate learning, and shallow learning
(b)human learning, animal learning, and robotics learning
(c)supervised learning, unsupervised learning, and reinforcement learning
(d)visual learners, reading learners, and writing learners

9.Supervised learning can be divided into:
(a)classification and clustering
(b)classification and regression
(c)clustering and regression
(d)classification, clustering, and regression

10.What is the goal of clustering?
(a)Group similar instances
(b)Predict numerical values for testing examples
(c)Reduce the number of features
(d)None of the above

Answers: 1. T 2. F 3. F 4. T 5. F 6. T 7. (a) 8. (c) 9. (b) 10. (a)