课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
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Challenge: Model building - SQL教程
课程: Complete Guide to AI and Data Science for SQL: From Beginner to Advanced
Challenge: Model building
(upbeat music) - [Instructor] So here's the scenario. Imagine you have built a linear regression model to predict the prices of used cars. You want to assess the model's performance and reliability. Now one of the assumptions you need to check is the mean residuals. Here is your challenge. Explain why checking the mean residuals is essential in assessing the accuracy of your car price prediction model. Take about 10 minutes for this challenge. Pause the video if needed. Once you've formulated your answer, hit play to see the solution in the next video.
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内容
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Creating the linear regression model and model summary: Part 19 分钟 33 秒
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Creating the linear regression model and model summary: Part 27 分钟 16 秒
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Creating the linear regression model and model summary: Part 35 分钟 33 秒
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Dropping insignificant variables and re-creating the model7 分钟 57 秒
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Checking assumptions for linear regression3 分钟 18 秒
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Assumption 1: Checking for mean residuals2 分钟 47 秒
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Assumption 2: Checking homoscedasticity3 分钟 13 秒
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Assumption 3: Checking linearity2 分钟 12 秒
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Assumption 4: Checking normality of error terms3 分钟 24 秒
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Q-Q plot for checking the normality of error terms3 分钟 14 秒
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Model performance comparison on train and test data6 分钟 7 秒
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Applying cross-validation and evaluation4 分钟 40 秒
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Challenge: Model building48 秒
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Solution: Model building1 分钟 16 秒
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