Difference between supervised and unsupervised learning, k means clustering, knn, SQL joins

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Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data. K-means clustering is a type of unsupervised learning algorithm. KNN is a supervised learning algorithm. SQL joins are used to combine data from multiple tables.

Supervised learning uses labeled data to train a model, while unsupervised learning uses unlabeled data
K-means clustering is a type of unsupervised learning algorithm that groups data points into k clusters based on similarity
KNN (K-Nearest Neighbors) is a supervised learning algorithm that classifies new data points based on the majority class of its k nearest neighbors
SQL joins are used to combine data from multiple tables based on a related column

Difference between supervised and unsupervised learning, k means clustering, knn, SQL joins

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