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5 cards from this section. Quick, good the night before a test.
What is a model in Machine Learning?
Think about what learns in the ML process.
Define input in the context of Machine Learning.
What do we provide to the model?
What does the term 'Model' refer to in Machine Learning?
Consider what part of ML reflects learning from data.
True or False: 'Input' refers to the results that a model gives after processing data.
Which part represents data given to the model?
Create a simple dataset with at least five examples of input-output pairs related to studying hours and marks. Then, describe how you would process this data for training a model.
Think about how to separate the hours from marks.
Discuss how different sources of input data can influence the output of a model, using an example from real life.
Which factors can change the reliability of your output?
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