Machine Learning: Clustering with K-Means
Offered By: Codecademy
Course Description
Overview
Use unsupervised learning to find patterns hidden in data.
Continue your Machine Learning journey with Machine Learning: Clustering with K-means. Spot patterns and identify classes with K-means clustering, and unsupervised machine learning technique.
* Spot groups in unlabeled data
* Build and assess K-means clustering algorithms
* Improve your model with K-means++
Continue your Machine Learning journey with Machine Learning: Clustering with K-means. Spot patterns and identify classes with K-means clustering, and unsupervised machine learning technique.
* Spot groups in unlabeled data
* Build and assess K-means clustering algorithms
* Improve your model with K-means++
Syllabus
- Clustering: K-Means: Clustering is the most well-known unsupervised learning technique. It finds structure in unlabeled data by identifying similar groups.
- Lesson: K-Means Clustering
- Quiz: K-Means Clustering
- Lesson: K-Means++ Clustering
- Project: Handwriting Recognition using K-Means
- Informational: Next Steps
Taught by
Nitya Mandyam
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent