Summary
Regression is a fundamental concept in machine learning used to predict a continuous outcome variable based on one or more predictor variables. It involves identifying the relationship between a dependent variable (often called the target) and one or more independent variables (features). We saw that, given our dataset, we were able to find correlations for certain variables. We also found that we could include columns like Date, but to include these, we needed to extract the important numerical parts from those columns, namely the year, month, and date.
Regression has many applications in other sectors, like healthcare and marketing. From a prompt perspective, it’s a good idea to set the context early on and show Copilot the shape of the data, which will then help you ask Copilot what to do next.
In the next chapter, we will use the same dataset while using GitHub Copilot to help us write some code.
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