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Question 3Which of the following is NOT an attribute of Machine Learning? 1 pointTakes data and answers as input and uses these inputs to create a set of rules that determine what the Machine Learning model will be Machine Learning defines behavioral rules by comparing large data sets to find common patternsTakes data and rules as input and uses these inputs to develop an algorithm that will give us an answerMachine Learning models can be continuously trained

Question

Question 3Which of the following is NOT an attribute of Machine Learning? 1 pointTakes data and answers as input and uses these inputs to create a set of rules that determine what the Machine Learning model will be Machine Learning defines behavioral rules by comparing large data sets to find common patternsTakes data and rules as input and uses these inputs to develop an algorithm that will give us an answerMachine Learning models can be continuously trained

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Solution

To answer this question, we need to identify which of the given options is NOT an attribute of Machine Learning.

Option 1 states that Machine Learning takes data and answers as input and uses these inputs to create a set of rules that determine what the Machine Learning model will be. This is a valid attribute of Machine Learning as it involves using data and answers to create rules for the model.

Option 2 states that Machine Learning defines behavioral rules by comparing large data sets to find common patterns. This is also a valid attribute of Machine Learning as it involves analyzing data sets to identify patterns and define rules.

Option 3 states that Machine Learning takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer. This is a valid attribute of Machine Learning as it involves using data and rules to develop an algorithm for generating answers.

Option 4 states that Machine Learning models can be continuously trained. This is a valid attribute of Machine Learning as it allows models to improve and adapt over time through continuous training.

Therefore, the answer is Option 2: "Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer" is NOT an attribute of Machine Learning.

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