Wayne Analytics

Project Portfolio



About Derek Wayne


I’m often asked why I decided to pursue data science just after graduating from film school. I can remember juggling video editing with calculus, and falling in love with integrals over flashy cuts. I was good at both but I really wanted to challenge myself academically, do something unexpected, and strive to overcome fears of failure. Fast forward to today, and data science has become a fundamental part of who I am, how I think, and how I approach problems. My absolute passion is to communicate parts of this exciting field to others; to both peers and laymen. What I can offer is a strong understanding of modern statistical practice, experience with relevant tools, and enthusiasm for every project I work on.


Methods of Cluster Analysis:
Comparing K-Means and EM

Cluster Analysis refers to the process of assigning objects to groups on the basis of some shared characteristics. It is extremely useful in exploratory data analysis. In this post I demonstrate the differences between two popular algorithms: k-means and expectation maximization, for solving the task.

Segmentation of Brain MR Images:
A modern approach to tissue classification

The problem of autonomous segmentation of brain tissues has led to research on complex algorithms that model the spatial relationships in three dimensional scans. Particularly it presents a fascinating study of graph partitioning methods. In this project I achieve an accurate segmentation of a full MRI scan of the brain using modern techniques.