Practice Machine Learning Basics (6) - Machine Learning Basics

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10 questions

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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define Machine Learning in your own words.
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Consider how machines interact with information.
Question 2.
What is the difference between supervised and unsupervised learning?
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Think about whether the data has pre-defined labels.
3Question 3.
What does Machine Learning allow systems to do?
- Automatically generate code
- Learn from data
- Control hardware
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Think about the core purpose of ML.
4Question 4.
What is the goal of supervised learning?
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Consider the relation of inputs with known outputs.
Question 5.
Design a supervised learning model for predicting whether an email is spam or not. Identify the key data features you would use and justify your choices.
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Think about common characteristics of spam emails.
Question 6.
Propose a method to structure a clustering analysis for customer segmentation using unsupervised learning. What data would you consider relevant?
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Consider what behavioral data reflects similarities among users.

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