Podcast: Play in new window | Embed
Subscribe: Apple Podcasts | Google Podcasts | Spotify | Amazon Music | Email | TuneIn | Deezer | RSS
The idea of grouping similar types of data together is the main idea behind clustering. Clustering supports the goals of Unsupervised Learning which is finding patterns in data without requiring labeled datasets. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Clustering, Cluster Analysis, K-Means, and Gaussian Mixture Model, and explain how they relate to AI and why it’s important to know about them.
Show Notes:
- FREE Intro to CPMAI mini course
- CPMAI Training and Certification
- AI Glossary
- Glossary Series: Artificial Intelligence
- AI Glossary Series – Machine Learning, Algorithm, Model
- Glossary Series: Prediction, Inference, and Generalization
- Glossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement Learning
- Glossary Series: Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision Boundary
- Glossary Series: Regression, Linear Regression
