Tennessee J Leeuwenburg
where else to find them
what they talk about
all 10 in the filters
where they keep going back
- PyCon AU7 editions2010–2026
- PyCon Australia Education Miniconf3 editions2013–2015
on a stage with
never shared a talk
who talks about the same things
- Evan Kohilas14 talks
- Noah Kantrowitz16 talks
- Nick Moore11 talks
- Katie Bell11 talks
- Harry Percival10 talks
- Mario Munoz12 talks
| title | conference | date |
|---|---|---|
| Why should I write software well? | PyCon AU 2026 | 2026-08-26 |
Argues that software quality is a time‑based tradeoff with concrete examples: adopting pydantic and dataclasses versus keeping fewer dependencies, prototyping… | ||
| PyEarthTools: Machine learning for Earth system science | PyCon AU 2025 | 2025-09-12 |
An open source Python framework for building and running machine learning Earth system models, PyEarthTools supplies modular data pipelines (reprojection… | ||
| "Making an open source package - lessons learned" | PyCon AU 2024 | 2024-11-22 |
Concrete lessons from building the open source package scores focus on what actually changed outcomes: using pyproject.toml for config, choosing hatch (but… | ||
| Verifying and evaluating scientific results with the open source package "scores" | PyCon AU 2024 | 2024-11-22 |
An open source Python package called "scores" claims to verify labeled n‑dimensional data at scale and actually implements over 50 metrics with per‑metric… | ||
| Making Codebases Easier to Learn and Maintain | PyConline AU 2020 | 2020-09-04 |
Shows concrete changes: docstrings that state purpose and why not just parameters, repo layout that pull tests out of source and separate interface from… | ||
| How to get everyone to get on board with software security: practical tips and suggestions. | PyCon AU 2019 | 2019-08-02 |
Claims concrete wins: someone forces deep test coverage in a legacy app at the cost of a three‑month delay to a massive project and it pays off; small… | ||
| Using Python in a Data Hackathon | PyCon AU 2017 | 2017-08-03 |
Shows a practical weekend workflow: prebuilt Anaconda/Jupyter shell scripts to avoid setup fights, use SQLite for portable ingestion, and prefer binary… | ||
| Syntax Hijacking: Genius or Evil? | PyCon AU 2017 | 2017-08-03 |
Builds a small wizardry library (code on GitHub) that literally rebinds indexing and printing, implements fuzzy lookup using Levenshtein distance scaled into a… | ||
| Data Science Design Patterns | PyCon AU 2016 Science and Data Miniconf | 2016-08-12 |
Claims that most data‑science projects reduce to a few repeatable patterns and demonstrates concrete ones: adapter pattern for hiding messy… | ||
| Applied Data Science | PyCon Australia 2015 | 2015-07-31 |
Walks through installing Anaconda/Miniconda and running IPython notebooks, trains a Random Forest (100 estimators → ~90% on MNIST), then builds a Keras neural… | ||
| Sprinting For Beginners | PyCon Australia 2015 | 2015-07-31 |
Explains how to start and run a community sprint with concrete steps: find the venue, label your table, add the project to the wiki, and welcome newcomers… | ||
| Verification: Truth in Statistics | PyCon Australia 2014 | 2014-08-01 |
Forecast verification compares forecasts to truth and shows concrete fixes: a consistent half a degree bias explains an easy RMSE improvement, an S1 skill… | ||
| Solving problems by sharing them... with Python! | PyCon Australia 2013 | 2013-07-05 |
Argues that sharing runnable artifacts and visual evidence reduces manager-developer disconnect, showing concrete wins: uses ipython notebook to load model… | ||
| Using Python for Natural Language Generation and Analysis | PyCon AU 2010 | 2010-06-26 |
Using Python for Natural Language Generation and Analysis
Presented by Tennessee J Leeuwenburg (Australian Government Bureau of
Meteorology)
Python is used… | ||
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