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https://opensea.io/collection/dev-21
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Supervised Learning Description: The model learns from labeled data, where both the input (features) and the output (target) are provided. The objective is to map inputs to the correct outputs. Common Use Cases: Spam email detection. House price prediction. Image classification. Examples: Linear Regression Logistic Regression Support Vector Machines (SVM) Neural Networks (when trained with labeled data) https://crazylittleprojects.com/how-to-use-sewing-machine/
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