Course : Cluster Analysis & Unsupervised ML in Python
Video Mins completed : 125 mins
Last Video # completed : 13
Notes
Clustering application
- Categorization
- Search : Closest neighbors for an item
- Density estimation : Finding probability distribution in the data.
Implemented exercises to understand the core logic of K-Means clustering. This was unnecessary. Implementation could have been skipped. Need to move faster.