Unsupervised Learning (Clustering)
Watch the K-Means algorithm discover hidden patterns step-by-step. Try different data shapes, adjust the number of clusters, use the elbow method to find the optimal K, and click on the chart to add your own data points.
Learn Unsupervised Learning on DataCamp
Curated courses and career tracks to take your understanding from this demo to real-world mastery. All links open directly on DataCamp.
Unsupervised Learning in Python
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
Cluster Analysis in Python
Master hierarchical clustering, k-means, and DBSCAN. Learn how to find the optimal number of clusters using dendrograms and elbow curves.
Dimensionality Reduction in Python
Explore PCA, t-SNE, and feature selection techniques to reduce dataset complexity while preserving structure.
Feature Engineering for Machine Learning in Python
Discover how to create better input features for supervised and unsupervised models using automated and manual techniques.
Introduction to Visualization with Matplotlib
Learn to create 2D visualizations to better explore and communicate cluster structure and high-dimensional data.
Machine Learning Scientist with Python
The complete path from supervised learning to advanced unsupervised techniques, deep learning, and big data.
