Learn Automated Data Analysis
Guides to the methods behind automated statistics — from exploratory analysis to model discovery, uncertainty and generated reporting.
Topic hubs
- Automated Data Analysis — what gets automated, and what does not
- AutoML — model selection, tuning and evaluation
- Time Series — trend, seasonality, changepoints, forecasting
- Gaussian Processes — kernels, uncertainty, compositional structure
- Bayesian Statistics — inference, model comparison, Occam’s razor
- Explainable AI — interpretability, auditability and model criticism
Where to start
If the subject is new, read What Is an Automatic Statistician? then How Automated Statistical Analysis Works. If you have a series in front of you, start with How Automated Time-Series Analysis Works.