Data, Stats, and AI Concepts
This repository is a curated collection of data, stats, and AI concepts drawn from highly cited research papers. Each note is a short, runnable Marimo notebook: the idea, the math, and a small experiment.
Currently working on: TabICLv2 — a tabular foundation model for in-context learning (classification and regression).
Notes are published at learnaiinminutes.com.
Running the notebooks
Dependencies are managed with uv. Python 3.10–3.12 is required. From the repo root:
uv sync
That creates .venv and installs everything, including Marimo.
uv run marimo edit
or a single file:
uv run marimo edit notebooks/fundamentals/applied-statistics/acf_and_pacf.py
notebooks/fundamentals/programming/optimization/cudf.py additionally needs Linux + CUDA 12:
uv pip install --extra-index-url https://pypi.nvidia.com cudf-cu12 "polars[gpu]"
Fundamentals
Notes that are not tied to a specific paper live in notebooks/fundamentals/. They cover stats, ML, deep learning, and generative-AI primitives.
Paper-specific work (starting with TabICLv2) will sit next to that folder.
Contributing
Contributions are welcome. Open an issue or a pull request if you have a concept, a paper, or a fix.
License
- Code is licensed under the MIT License.
- Content (text, explanations, visualizations) is licensed under Creative Commons Attribution 4.0 (CC BY 4.0). You may reuse it with attribution.
Contact
Email: [email protected]
Threads: @AIinMinutes