MLE4: Unsupervised Learning
In this course, instructor Asha Saxena explores unsupervised learning in detail. She covers dimensionality reduction, feature selection and extraction, PCA, clustering, Hartigan-Wong algorithms, cluster validation, Gaussian mixture models, rules in data mining, and much more.
In this course, instructor Asha Saxena explores unsupervised learning in detail. She covers dimensionality reduction, feature selection and extraction, PCA, clustering, Hartigan-Wong algorithms, cluster validation, Gaussian mixture models, rules in data mining, and much more.
Purpose
To gain a deeper understanding of the usage of the many components and variables involved in unsupervised learning.
Outcome
- Understand unsupervised learning and how it is used
- Explore the many different types of unsupervised learning components
This Course Includes:
- A 53-minute educational training video
- A 16-question exam
- Self-paced and on-demand e-learning
- Unlimited course access
- Course CEUs: 1
Individual Course Price: $99
Learning Plan Price: $499
Learning Plan CEUs: 6
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