What is the difference between Supervised and Unsupervised Learning
The primary differences between supervised and unsupervised learning is the presence or absence of labeled data for training
The primary differences between supervised and unsupervised learning is the presence or absence of labeled data for training
Clustering is used to partition data set into N distinct groups/clusters. These groups are semantically coherent in nature
In unsupervised learning the algorithms are not given any labeled data but instead the goal is to find patterns and relationships that are hidden in the input data.
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