Clustering

ELI5 — The Vibe Check

Clustering is teaching an AI to find groups in data WITHOUT being told what the groups are. You dump in a million customer records and say 'find the natural groups.' The algorithm discovers that there are 5 types of customers you never knew about. It's unsupervised — nobody tells it what to look for.

Real Talk

Clustering is an unsupervised learning task that groups data points by similarity without predefined labels. Common algorithms include K-means, DBSCAN, hierarchical clustering, and Gaussian Mixture Models. It is used for customer segmentation, anomaly detection, and data exploration. Evaluation is less straightforward than supervised tasks.

Show Me The Code

from sklearn.cluster import KMeans
kmeans = KMeans(n_clusters=5, random_state=42)
kmeans.fit(X)
labels = kmeans.labels_  # which cluster each point belongs to

When You'll Hear This

"We used clustering to discover customer segments." / "Clustering found 3 natural groups in the user behavior data."