Recall & Review
beginner
What is the first step in the ML workflow?
The first step is collecting data. This means gathering the information or examples the model will learn from.
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beginner
Why do we prepare data before training a model?
Preparing data means cleaning and organizing it so the model can learn better. It helps remove mistakes and makes data easier to understand.
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beginner
What happens during the training step in ML?
During training, the model looks at the data and learns patterns. It adjusts itself to make better predictions.
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beginner
How do we know if a model is good after training?
We evaluate the model by testing it on new data and checking how well it predicts. This tells us if the model learned well.
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beginner
What does deploying a model mean?
Deploying means putting the model into use so it can help in real life, like in an app or website.
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What is the main goal of the data preparation step?
Which step comes right after training a model?
What does deploying a model allow you to do?
Why is collecting good data important?
Which step involves checking model predictions on new data?
Describe the five main steps of the ML workflow and why each is important.
Explain how data preparation affects the training and evaluation steps in ML.