As an exercise, or even to solve a relatively simple problem, many of you may have implemented linear regression with one feature and one target. However, in the real world, most machine learning problems require that you work with more than one feature.
For example, to calculate an individual’s home loan eligibility, we not only need his age but also his credit rating and other features.
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