Page 46 - AI & Machine Learning for Beginners: A Guided Workbook

Question (Evaluation & Parameter Tuning): What is

the purpose of the evaluation phase in AI model training,
and how does it help determine the model’s readiness for
real-world data?
Follow-up: What are hyperparameters, and why is tuning
them critical to the overall model performance?
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Question (Analogy to Human Learning): The

training process is compared to learning how to drive a car.
How does this analogy help you understand the concept of
iterative improvement in model training?
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Reflect on these questions to ensure you’ve grasped the core
concepts of data collection, model selection, training, evaluation,
and tuning in AI. Feel free to refer back to the example for clues and
detailed explanations!

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