Tutorials#
Comprehensive step-by-step guides that walk through complete workflows and real-world scenarios. These tutorials help you learn TanaT systematically by combining multiple concepts into practical examples.
Building & Ingesting Data#
Master the builder API and load data from multiple heterogeneous sources:
Building pools from multiple sources: combine Parquet and CSV sources into a single pool, configure builder options, compose trajectory pools, and manage the workspace
Real-World Applications#
End-to-end workflows on real datasets:
MIMIC-IV: Clinical Cohort Analysis
MIMIC-IV: Clinical Cohort Analysis · A series of tutorials on the MIMIC-IV demo dataset:
Exploring a patient cohort: load, inspect, visualise, train/test split
Filtering and preparing a cohort: criteria, T0 anchor, relative window
Analysing and clustering a cohort: distance matrix, hierarchical clustering, faceted timeline
Survival analysis by admission cluster: mortality endpoint, survival target, per-cluster Kaplan-Meier curves
Learning clinical phenotypes with SWoTTeD: OHE tensor, dictionary learning, phenotype interpretation
Education: Learning Session Analysis
MOOC: Learning Session Analysis · A series of tutorials on the MOOC demo dataset:
Exploring learner activity sequences: load, inspect, visualise, train/test split
Clustering sessions by action patterns: criteria, T0 anchor, relative window
Time Series to Sequences#
Discretizing time series into sequences: apply Aeon segmentation/quantization methods to raw time series and ingest the result as a TanaT sequence pool
See Also#
First Steps: Starting point before diving into tutorials.
Core Concepts: TanaT data model explained.
Builder & Storage: Builder API reference (source methods, options, workspace).
Data Manipulation: All operations on pools and sequences.
API Documentation: Full API reference.