Category: Unsupervised Learning
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Clustering Use Cases – Unsupervised Machine Learning on GCP
Clustering is one of the most common patterns in Unsupervised machine learning. Some areas / use cases where we can apply clustering include: Market segmentation Social network analysis Search result grouping Medical imaging Image segmentation Anomaly detection BigQuery ML: Is ideal for clustering use cases (and SQL-based machine learning use cases). Apart from BQML, GCP…
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K-Means Clustering Use Cases
K-Means Clustering Purpose: K-means is an unsupervised learning algorithm used for clustering data into a predefined number of clusters (k). How It Works: Initialization: Select k initial cluster centroids randomly. Assignment: Assign each data point to the nearest cluster centroid. Update: Recalculate the centroids of the clusters based on the assigned data points. Iterate: Repeat…