AI & Data
This trunk focuses on durable ideas rather than model release timelines. It connects learning theory and model architectures with the data, evaluation, and tools needed to make intelligent systems useful.
Branches
| Branch | Focus |
|---|---|
| Machine Learning | Supervised learning, statistical models, and general learning concepts |
| Deep Learning | Neural architectures, attention, transformers, and generative models |
| Data Science | Datasets, analysis tools, visualization, and practical workflows |
The Supporting Network
AI notes are intentionally connected to other trunks:
- Mathematics provides linear algebra, probability, calculus, and optimization.
- Computer Science provides algorithms, data structures, and implementation foundations.
- Tools & Workflows provides environments, notebooks, version control, and reproducible practice.
Expansion Rule
New model announcements do not automatically become permanent notes. A topic earns a place here when it contributes a reusable concept, architecture, evaluation method, or implementation pattern.