Event Time
Event Time in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Data contracts, ownership, and lineage
A trustworthy dataset explains meaning, accountability, and ancestry—not just columns.
Data & feature foundationsPoint-in-time-correct features
Point-in-time correctness preserves the knowledge boundary of the original decision.
Data & feature foundationsFeature transformations that survive production
Ship the fitted representation contract with the model, in the same order and with the same edge cases.
Sequence ML: RNNs, GRUs & LSTMsSequences are not IID
In sequence learning, chronology is part of the feature schema: define the cutoff first, then construct inputs, labels, and splits around it.
Sequence ML: RNNs, GRUs & LSTMsRecurrent state and BPTT
Recurrent state carries information forward; BPTT carries responsibility backward, and truncation decides how far that responsibility can travel.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.