The clustering self-study is an implementation-oriented introduction to clustering.
This course is not:
- an exhaustive review of clustering
- an exhaustive description of and comparison between different algorithmic approaches to clustering
- a course on clustering with TensorFlow
- a tutorial on classification (as opposed to clustering)
This course assumes you have:
- Completed Introduction to Machine Learning Problem Framing or have equivalent knowledge.
- Completed Machine Learning Crash Course or have equivalent knowledge.
- Completed Data Preparation and Feature Engineering or have equivalent knowledge.
- Basic knowledge of data distributions, such as Gaussian and power law distributions.
- Basic programming knowledge in Python.