Polynomial linear regression using Sklearn is tedious as one has to explicitly code its features. This can get challenging when one has to iteratively build higher-degree polynomial models. NumPy's 𝐩𝐨𝐥𝐲𝐟𝐢𝐭() method is an excellent alternative to this. Here, you can specify the degree of the polynomial as a parameter. As a result, it automatically creates the corresponding polynomial features.