Cats Vs Dogs? Let's make an AI to settle this (LAB)

The video explores using AI to decide between adopting a cat or a dog. It covers building a simple AI model using Python and Google Collaboratory, collecting data through surveys, and testing the model's accuracy. The video highlights issues of bias in AI, particularly how data collection can skew results, and discusses methods to identify and correct these biases to improve model accuracy.

What factors did the teacher consider when deciding to adopt a pet?

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How did the teacher plan to gather data about pet happiness?

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What was the purpose of the survey conducted by the teacher?

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What programming language and tool did the teacher use for the AI model?

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What were the main features considered in the AI model to predict happiness?

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What issues did the teacher encounter with the AI model's predictions?

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What conclusions did the teacher draw from the survey results regarding pet happiness?

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What is the significance of ensuring a balanced dataset in AI training?

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How did the teacher plan to address the bias in the survey data?

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What steps did the teacher outline for improving the AI model?

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