Machine Learning
Unsupervised Learning and Clustering
Navigate through the intricacies of Unsupervised Learning and Clustering in this hands-on course. Skip the high-level libraries and build core aspects of unsupervised learning methods from scratch, including k-Means, mini-batch k-Means, Principal Component Analysis, and DBSCAN. Learn to assess cluster quality with crucial clustering metrics like homogeneity, completeness, and v-metric.
C++
4 lessons
15 practices
3 hours
Course details
Unsupervised Learning with Clustering
Customer Segmentation Using k-Means Clustering
Exploring Three-Cluster K-Means Algorithm
Updating Centroid of a Data Cluster
Updating Centroids in k-Means Algorithm
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