Example 2Lesson 27Free preview

Ex2 Intro

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

Summary

The second example predicts the price of a home from several features at once, such as the area, the number of rooms, and the age of the building. Since the output is a continuous number, this problem includes regression. The model receives larger dimensional input than the first example that has only one feature.

Key points

Example 2 predicts the price of a home from many features at once.
Each data line represents a single house with several characteristics.
House prices are a continuous expense so that includes a problem of regression.
The tensor features are shaped [number of houses, number of features].

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