Description
Machine learning models thrive on numbers. But what happens when your data includes categories like colors, countries, or job titles? These categorical variables, expressed in text form, need a translation to join the numerical party. Imagine trying to bake a cake with a recipe that lists ingredients as “sweet,” “red,” and “powdery” – you need precise measurements!
Here are the essential techniques for encoding categorical data, transforming those text-based categories into numerical representations that your AI models can digest. Plus various encoding methods, their strengths, and how to choose the right approach for your specific needs. Get ready to unlock the power of your categorical data and fuel your machine-learning success.
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