PyData Indy 2019
2019-10-11
Indianapolis, United States
who it's for
data scientists, python developers, machine learning engineers, research computing staff, data engineers, devops engineers, analytics managers
topics
Jupyter in Visual Studio Code; dockerized Jupyter images; Apache Airflow workflows; scikit-learn model pipelines; TensorFlow and PyTorch GPUs; automated feature transforms; reproducible remote notebooks; NIST big data reference implementation; CI/CD for containerized services; industry 4.0 predictive maintenance; model fairness and adversarial issues; healthcare machine learning constraints
| title | author | length |
|---|---|---|
| Road Warrior Developer | Calvin Hendrix-Parker | 06m |
Claims that a laptop can be left home by showing a reproducible setup: iPad Pro with USB C plus a 40-percent keyboard and a dongle that carries HDMI and USB… | ||
| Big Taco Data | Chris Pfeiffer | 05m |
Vertical integration yields measurable differences: a machine learning wait-time model predicts delivery times with about a 4.5 minute average error because… | ||
| Making AI More Accessible to the Non-Developer | Robert Herbig | 06m |
Claim: non-developers use ML workflows without writing code by providing clearer APIs and automation. Concrete work: wrapped scikit-learn and TensorFlow in… | ||
| Jupyter Notebooks in Visual Studio Code | Felix Wyss | 07m |
Visual Studio Code now offers native Jupyter support that launches a kernel and connects to local or remote runtimes, runs cells inline, and shows images and… | ||
| What is Machine Learning, and How Do I Get Started? | Alyssa Batula | 40m |
Clear checklist: justification for ML (when a human labels something in under a second), mindset shift away from line‑by‑line coding, concrete data rules of… | ||
| Deep Learning Support at Indiana University | Ben Fulton | 34m |
Indiana University adds a 12-node expansion to the Carbonate cluster with eight nodes sporting dual P100 NVIDIA GPUs and four with dual V100 GPUs, exposes… | ||
| Data Analytics with the Big Data NIST Reference... | Gregor von Laszewski | 51m |
Volume 8 of the NIST Big Data Reference Architecture is accepted last week and a working reference implementation exists: a pipeline converts the OpenAPI 3.0… | ||
| State of Modern Programing | Justin Bolles | 20m |
Argues that containers let each language do its job and shows a real pipeline that collects 16 data sources, pipes them through Python processing into a… | ||
| Artificial Intelligence: The Future of Healthcare | Kristin Day | 41m |
Concrete examples and concrete fixes are here: an Amazon resume filter that learned to downgrade women, a Roomba turned off its camera because of a poorly… | ||
| Use Apache-Airflow to Build Data Workflows | Luther Hill | 38m |
Claims a reproducible, versioned pipeline built with python and Apache-Airflow that replaces brittle cron jobs and tracks state in a metadata database… | ||
| How to Roll your own Dockerized Jupyter Environment | Paul Buis | 36m |
Builds a reproducible, cloud-hostable Jupyter notebook image using Docker and the Anaconda stack, with a Dockerfile that exploits layer caching and avoids… | ||
| Business Impact of Industry 4.0 | Reg Montague | 41m |
High-level survey of Industry 4.0 but with concrete claims: examples of manufacturers achieving measurable gains like $40M saved from reduced downtime… | ||
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