Technical Workshop Series - K-means Clustering for Data Analysis (2nd Offering)

Unlock the potential of unsupervised learning with this workshop on K-means clustering! Dive into clustering algorithms and see how K-means reveals hidden patterns in your data. With a mix of theory and real-world examples, you'll leave equipped to use K-means effectively in your projects. Demystify clustering and start making data-driven decisions!

 

1. Introduction to Clustering

2. Understanding K-means Clustering

3. Implementation of K-means

4. Evaluation of K-means Clustering

5. Practical Applications and Examples

6. Tips and Best Practices

7. Q&A Session

8. Conclusion

 

• Basic understanding of machine learning concepts

• Familiarity with data analysis principles

• Interest in learning about clustering algorithms and their applications

 

Nahid Abdolrahmanpour is a Ph.D. Student in Computer Science at the University of Windsor. They have a solid foundation in Data Mining and Artificial Intelligence with a research focus on So-cial Network Analysis, and a Master's degree in Computer Science specializing in Data Mining.