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Introduction to Clustering - Google Developers
Objectives:
- Describe clustering use cases in machine learning applications.
- Choose the appropriate similarity measure for an analysis.
- Cluster data with the k-means algorithm.
- Evaluate the quality of clustering results.
- Reduce dimensionality in clustering analysis with an autoencoder.
Prerequisites
This course assumes you have the following knowledge:
- Introduction to Machine Learning Problem Framing or equivalent.
- Machine Learning Crash Course, including Working with numerical data and Datasets, generalization, and overfitting, or equivalent.
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Resource details
| Contributed by: | Generative AI |
| Authored by: |
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| Licence: | More information on licences |
| Last updated: | 22 September 2025 |
| First contributed: | 02 July 2025 |
| Audience access level: | Full user |
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