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 😄.
- 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.
- Pathfinding: rewrite a proper introduction - review common graph issues.
- Pathfinding: can we do better then Djikstra?
- Pathfinding: even more topics!
- 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