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Lesson 8 — One-hot encoding
Turning categories into numbers
Models only understand numbers, but lots of data is categorical — words like "red", "green", "blue". One-hot encoding turns a category into a list of 0s with a single 1 in the position of that category. The list of all possible categories is called the vocabulary.
vocab = ["red", "green", "blue"]
# "green" -> [0, 1, 0]
Why not just red=1, green=2, blue=3? Because then the model would think blue is "bigger" than red, which means nothing.
Why it matters: almost every real dataset has categories (country, product type, weekday), and one-hot is the standard first way to feed them to a model.
Finish one_hot(value) with a list comprehension: 1 where the vocabulary item equals value, else 0.
Run your code — when the output matches the task, you will see a green check. Then mark the lesson complete.
Test your knowledgeA quick 3-question quiz on this lesson — instant feedback.