Introduction to Machine Learning - Chapter 1 Quiz

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16 Questions

What is the purpose of classification in machine learning?

To have predefined classes/labels and train a model to predict the class label of new data.

Give an example of a task that falls under identification in machine learning.

Face recognition

What is the primary objective of regression in machine learning?

To predict numerical values rather than class labels.

Explain the primary purpose of clustering in machine learning.

To group data points into clusters or groupings.

Provide an example of a task that involves recognition in machine learning.

Speech recognition

When is machine learning used as opposed to traditional programming?

When human expertise does not exist, humans are unable to explain their expertise, the solution changes in time, or the solution needs to be adapted to particular cases.

What is the main goal of machine learning?

Optimize a performance criterion using example data or past experience.

Give an example of a classification application.

Credit scoring

What is the role of statistics in machine learning?

Inference from a sample

What is the primary difference between data and knowledge in the context of machine learning?

Data is cheap and abundant; knowledge is expensive and scarce.

What is the process of extracting usable data from a larger set of raw data called?

Data mining

What are the main applications of machine learning in medicine?

Medical diagnosis

Give an example of an unsupervised learning application.

Association

What is the aim of building a model in machine learning?

To create a good and useful approximation to the data.

What does the term 'classification' refer to in machine learning?

Aka pattern recognition

Give an example of a market basket analysis association.

P (chips | beer) = 0.7

Test your understanding of the concepts covered in Chapter 1 'Introduction' of the book 'Introduction to Machine Learning 2nd Edition' by Ethem Alpaydin. This quiz covers topics such as classification, identification, and regression in the context of machine learning.

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