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Our Courses
Machine Learning and Data Science
Unsupervised Learning Techniques
Topics Covered
Level :
Intermediate
Clustering, dimensionality reduction, advanced applications
Course Summary
Apply clustering methods and dimensionality reduction to extract insights from unlabeled data.
Course Description
Participants will learn to uncover hidden structures in data without supervision using techniques like K-Means, PCA, and t-SNE.
Learning Modules
Module 1: Identifying problems suitable for unsupervised learning.
Module 2: Performing clustering and dimensionality reductio.
Module 3: Using unsupervised models in exploratory data analysis.
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