Multidimensional Datasets you own this product

prerequisites
basic Java • simple data structures • basic debugging
skills learned
multi-dimensional datasets and data structures • dimension reduction and distance function • K-Nearest-Neighbors algorithm
Yu Zhang and Mathias Funk
1 week · 8-12 hours per week · ADVANCED
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Look inside
In this liveProject, you’ll implement a multi-dimensional dataset and visualize it using dimension reduction on a Processing canvas. Dimension reduction helps select the most important features of a dataset, and is useful in machine learning. You’ll then explore distance functions and the k-Nearest-Neighbors algorithm to classify a new element.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project authors

Mathias Funk
Dr. Mathias Funk is an Associate Professor in the Future Everyday group in the Department of Industrial Design at the Eindhoven University of Technology. He has a background in Computer Science and a Ph.D. in Electrical Engineering from Eindhoven University of Technology. Since 2011, he has taught creative programming, computational prototyping, and designing with data and connectivity, and built tools for design researchers.
Yu Zhang
Dr. Yu Zhang has a background in fine arts and design. Her PhD research investigates the theory and artistic practice of interactive technologies for public, large-scale installations. As a researcher and artist, she approaches visual art with mixed reality installations and projections, sensor-based interactives, and computational arts. She has been teaching design and art in international workshops and higher education for over ten years.

prerequisites

This liveProject is for software developers, tech educators, and aspiring programmers who know the basics of Java programming. Some experience with Processing will be helpful, but is not required. To begin this liveProject you will need to be familiar with:

TOOLS
  • Basic Java skills such as variables and functions, control structures, if statements, and loops
TECHNIQUES
  • Simple data structures
  • Simple object-oriented programming
  • Basic debugging using print statements and the Processing console

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