CS-GY 9223: Course Resources

Visualization Libraries and Tools

JavaScript/Web-based

  • D3.js - Data-Driven Documents library (primary tool for course)
  • Vega-Lite - High-level grammar of interactive graphics
  • Observable - Interactive JavaScript notebooks
  • Plotly.js - Scientific charting library
  • Three.js - 3D graphics for neural network visualization

Python Libraries

Machine Learning Visualization Tools

Model Interpretation

  • SHAP - SHapley Additive exPlanations
  • LIME - Local Interpretable Model-agnostic Explanations
  • What-If Tool - Google’s model exploration tool
  • InterpretML - Microsoft’s interpretability toolkit
  • Captum - PyTorch model interpretability

Deep Learning

Dimensionality Reduction

Datasets

Machine Learning Datasets

Benchmark Datasets for Visualization

  • MNIST - Handwritten digits (good for dimensionality reduction)
  • CIFAR-10/100 - Image classification (good for CNN visualization)
  • 20 Newsgroups - Text classification (good for NLP visualization)
  • Iris/Wine/Titanic - Classic datasets for basic ML visualization

Research Papers and Surveys

Key Surveys

  • Hohman et al. “Visual Analytics in Deep Learning: An Interrogative Survey” (2018)
  • Liu et al. “Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective” (2017)
  • Yuan et al. “A Survey of Visual Analytics Techniques for Machine Learning” (2020)

Conference Venues

  • IEEE VIS - Premier visualization conference
  • CHI - Human-Computer Interaction
  • EuroVis - European visualization conference
  • ICML/NeurIPS - Machine learning conferences with vis components

Online Tutorials and Courses

D3.js Learning

Machine Learning Visualization

Development Tools

Debugging Tools

  • Chrome DevTools for JavaScript debugging
  • Python debugger (pdb) or VS Code debugger
  • Network tab for API debugging

Color Resources

Accessibility Resources

Community and Help

Course-specific

  • Discord Server: [Join link will be provided]
  • Office Hours: See course schedule
  • Brightspace: For assignment submission

Online Communities

Books and References

  1. “Visualization Analysis and Design” by Tamara Munzner
  2. “The Grammar of Graphics” by Leland Wilkinson
  3. “Interactive Data Visualization for the Web” by Scott Murray
  4. “Information Visualization: Perception for Design” by Colin Ware
  5. “The Visual Display of Quantitative Information” by Edward Tufte

Online Books

Example Projects and Inspiration

Galleries

ML Visualization Projects

Citation Management

For your projects and papers:


This resource list will be updated throughout the semester. Please suggest additional resources on Discord!