Eric J. Ma
where else to find them
what they talk about
all 6 in the filters
where they keep going back
- PyCon US3 editions2020–2022
on a stage with
never shared a talk
who talks about the same things
- Paco Nathan8 talks
- Vincent D Warmerdam22 talks
- Cheuk Ting Ho61 talks
- Andreas Kollegger16 talks
- Jennifer Reif9 talks
- Stephen Chin54 talks
| title | conference | date |
|---|---|---|
| Building LLM Agents Made Simple a | PyData Boston 2025 | 2025-12-08 |
A hands‑on build of a back‑office automation system using LlamaBot inside Marimo notebooks maps workflows into three concrete agents: receipt processor that… | ||
| Patterns for Productive Agent-Assisted Programming | PyData Boston 2025 | 2025-12-08 |
Claims a repeatable four-step workflow—plan your changes, write tests first, let the agent build, document what you created—and shows it on a real repo using… | ||
| Network Analysis Made Simple | PyCon US 2022 | 2022-04-27 |
Hands-on tutorial that actually shows code and results: builds reproducible notebooks with networkx and nxvis, loads real datasets (a 29‑node seventh‑grade… | ||
| Magical NumPy with JAX | PyCon US 2021 | 2021-05-14 |
Claim: write idiomatic NumPy and get autodiff, JIT and parallelism without learning a new array library. Demos use the NumPy‑compatible JAX API with vmap… | ||
| A careful walk through probability distributions, using Python | PyCon US 2020 | 2020-04-15 |
Python code and SciPy.stats power an interactive Streamlit app at python-prob.ericmjl.com that constructs a Gaussian class with mu=1.7 and sigma=2.4… | ||
| Demystifying Deep Learning for Data Scientists | PyCon US 2020 | 2020-04-15 |
Shows how to implement linear, logistic and feed‑forward networks from first principles using NumPy-style code and Jax automatic differentiation, with working… | ||
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