Unsupervised Learning: Clustering

AI, ML colleagues, this  program will focus on Unsupervised Learning Clustering algorithms and methods for Machine Learning through practical examples and code. The course has code and sample data for you to run and learn from. It also encourages you to explore your own datasets using Clustering algorithms. Students who are interested in a practical introduction to clustering, a kind of unsupervised machine learning. Want an intuitive understanding of the theory behind clustering. Students can use these methods and algorithms for hot applications such as marketing analytics, customer segmentation, anomaly detection, fraud detection, and other practical applications in their respective fields. Skill-based training modules address: 1) K-Means Clustering, 2) Gaussian Mixture Models (GMMs), 3) Hierarchical Clustering, 4) Methods for Selecting Number of Clusters, 5) Evaluating the Quality of the Clustering, 6) Industry Applications, 7) Mini-Project: Pulling It All Together, and 9) Mini-Project Solution Preview, and 10) Solution Preview.

Enroll today (individuals & teams):https://tinyurl.com/rm6rx5v  

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (AIA)