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Visualizing Algorithms

Multidimensional Datasets

This project is part of the liveProject series Visualizing Algorithms.
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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liveProject This project is part of the liveProject series Visualizing Algorithms. liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $19.99 $29.99 you save: $10 (33%)
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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.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

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 Ph.D. 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

you will learn

This liveProject is an ideal preparation for programming interviews, whiteboarding exercises, computer science studies, and visual communication skill improvement. You’ll deepen your programming skills with a better understanding of common algorithms.

  • Multi-dimensional datasets and data structures
  • Dimension reduction and distance function
  • K-Nearest-Neighbors algorithm

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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