Answer / Ashish Kumar Singh

Supervised learning is generally more effective for image classification because it uses labeled data. The model learns from the pre-existing labels, making it capable of classifying images accurately. In contrast, unsupervised learning does not use labeled data and relies on finding patterns within the data itself, which can lead to less accurate results, especially when dealing with complex image datasets.

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