Example 2Lesson 28Free preview

Ex2 Data

This lesson is part of A.I. · All levels

Summary

Before practicing a home price model, the data was normalized by dividing each value by its maximum value so that it was in the range of 0 to 1. The data is also divided into training and testing sections so that the model's capabilities on the new data can be measured. Normalisation makes training more stable and converges faster.

Key points

Normalisation divides the value by the maximum so that the result is in the range of 0-1.
Features with different scales can make training unstable.
The data is divided into training for learning and testing for evaluation.
The same maximum value is used when predicting new data to be consistent.

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