One Hot Encoding Explained | Built In
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One Hot Encoding Explained | Built In
One hot encoding is a machine learning technique that encodes categorical data into numerical ones. Here’s how to apply it in Scikit-Learn and Pandas.
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OpenCV University on Instagram: "🔢 One-Hot Encoding ㅤ Classes are represented as vectors. Only one value is 1, the rest are 0 — indicating the correct label. ㅤ That’s why it’s called one-hot. Simple, but essential for classification models. ㅤ #MachineLearning #DeepLearning #AI #DataScience #ComputerVision #NeuralNetworks #MLBasics #AIEducation"
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OpenCV University on Instagram: "🔢 One-Hot Encoding ㅤ Classes are represented as vectors. Only one value is 1, the rest are 0 — indicating the correct label. ㅤ That’s why it’s called one-hot. Simple, but essential for classification models. ㅤ #MachineLearning #DeepLearning #AI #DataScience #ComputerVision #NeuralNetworks #MLBasics #AIEducation"
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Dev Anand on Instagram: "One-hot encoding converts categories into separate binary features so models treat each category independently, without assuming any order."
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