AI engineering glossary · Time series recsys
What is patchTST?
PatchTST: A Transformer-based forecasting model that splits each series into patches, treats each as a token, and models each channel independently. Patching shortens the sequence and lets attention cover longer history.
PatchTST: an example
A 512-step history cut into patches of 16 steps yields 32 tokens for attention.
Related terms
More Time series recsys terms
- Pointwise ranking
- Popularity bias
- Prediction interval
- Probabilistic forecasting
- Prophet
- Quantile forecast
- Random walk
- Ranking stage
Where you learn it
PatchTST is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.