You have better/fun ideas? Please tell me!

Here is my current backlog. Don’t hesitate to comment and tell me what you are most interested in 😄.

Unpublished drafts

  • Why do we do regularization in machine learning?
  • How to visualize many time series at the same time (expect some new stuff).
  • Tools for clustering + auto summarization, like Ayasdi.
  • Algorithms exploiting the intrinsic dimension of data
  • Optical modulation (part II+).
  • tSNE+streaming (part II+).
  • Linear Programming for optical network optimization.

map of topics and useful algorithms for pathfinding

  • Dependency graphs: where and how can we use them? (#migration)
  • Anomaly detection: why it’s not simple.
  • 10 tips for beautiful data visualizations.
  • Comparing machine learning models.
  • Dealing with high cardinality features
  • Feature engineering checklist