- Type Validation
- Level Intermediate
- Time Days
- Cost Paid
This badge earner comprehends unsupervised learning and its applications, including clustering with k-means. They grasp computational challenges in clustering algorithms and methods to overcome them, comparing and selecting techniques suitable for data. Moreover, they are familiar with dimensionality reduction methods such as Principal Component Analysis, Kernel Principal Component Analysis, and matrix factorization for managing big data and text mining tasks.
- Type Validation
- Level Intermediate
- Time Days
- Cost Paid
Skills
Earning Criteria
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Pass the Coursera course assessment criteria.