COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Modern AI applications
|
|
|
Face detection
|
|
|
Object detection
|
|
|
All of the above
|
Detailed explanation-1: -Unsupervised learning is commonly used for finding meaningful patterns and groupings inherent in data, extracting generative features, and exploratory purposes.
Detailed explanation-2: -Twin sample validation can be used to validate results of unsupervised learning. It should be used in combination with internal validation. It can prove to be highly useful in case of time-series data where we want to ensure that our results remain same across time.
Detailed explanation-3: -The number one advantage of unsupervised learning is the ability for a machine to tackle problems that humans might find insurmountable either due to a limited capacity or a bias. Unsupervised learning is ideal for exploring raw and unknown data.
Detailed explanation-4: -Some examples of unsupervised learning algorithms include K-Means Clustering, Principal Component Analysis and Hierarchical Clustering.