Conferences / PyData
PyData NYC 2022
Nov 9–11, 2022 · Microsoft Conference Center, Times Square (11 Times Sq), New York, NY, United States
- Conference
- PyData Data science & ML
- Dates
- Nov 9, 2022 – Nov 11, 2022
- Venue
- Microsoft Conference Center, Times Square (11 Times Sq)
- Place
- New York, NY, United States
- Format
- In person
- Status
- Past
- Attendance
- —Tickets page states conference passes sold out; no headcount published.
- Website
- pydata.org
- Recorded
- 18 sponsors · 64 speaker appearances
- Notes
- Talks Nov 9-10, tutorials Nov 11. Tickets were sold via Eventbrite; prices not recovered. Speakers: the pretalx site (nyc2022.pydata.org/cfp) is offline; 32 archived talk pages give names and bios, the rest of the list is reconstructed from the official PyData NYC 2022 YouTube playlist titles (names as given there, affiliation null). Recorded talks whose titles give only surnames (e.g. 'Peterson & Qin', 'Song & Srinivasan', 'Naziga+Qazi', 'Kravchenko + Doest') are omitted, as are unrecorded talks, so the list is incomplete. Keynote affiliations from pydata.org/nyc2022. The pretalx bio shown for Jules S. Damji describes Richard Liaw (Anyscale), so his affiliation is left null. Alex Merose's affiliation (Google Research, Anthromet team 2021–2023) is from his CV, https://alex.merose.com/cv/, after a user correction.
Ticket prices
No ticket prices recorded
Sponsors 18
Title / headline 4
- Anaconda · Diamond
- CVS Health · Diamond
- Microsoft · Host
- Noteable · Diamond
Community 2
Speakers and talks 64
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Chelle Gentemann | NASA | Keynote | Keynote - I'm from the government and I'm here to help | Video |
| Melissa Mendonça | Quansight | Keynote | Keynote - Can we optimize communities? | Video |
| Paul Romer | New York University | Keynote | — | — |
| Thomas Caswell | Brookhaven National Laboratory | Keynote | From Science to Open Source and Back Again | Video |
| Adam Lewis | — | Speaker | Scaling Python - Bank Edition | Video |
| Alex Merose | Speaker | Apache Beam on Dask- Portable, Scalable, Scientific Python | Video | |
| Allen Downey | DrivenData | Speaker | Chasing the Overton Window | Video |
| Andrew Fulton | — | Speaker | Scaling Python - Bank Edition | Video |
| Anirrudh Krishnan | Quansight | Speaker | Scaling Python - Bank Edition | Video |
| Benjamin Batorsky | Institute for Experiential AI | Tutorial | Bagging to BERT: A tour of applied NLP | Video |
| Brian Bush | — | Speaker | Practical MLOps- Do we need all the things | Video |
| Cheuk Ting Ho | — | Speaker | Using Numba Effectively Today | Video |
| Cheuk Ting Ho | — | Speaker | I hate writing tests, that's why I use Hypothesis | Video |
| Colin Carroll | Speaker | JAX for Bayes | Video | |
| Dagshayani Kamalaharan | — | Speaker | Serving Pytorch Models in Production | Video |
| Daniel Chen | University of Washington | Speaker | Install Python. Quarto Render All the Things | Video |
| Diego Torres Quintanilla | — | Speaker | How we upstreamed our internal goals to JupyterLab 4 | Video |
| Elijah ben Izzy | — | Speaker | Scalable Feature Engineering with Hamilton | Video |
| Eskild Eriksen | Quansight | Tutorial | Nebari: Easily deploy and maintain an open source data science platform on the cloud of your choice | Video |
| Estefania Barreto-Ojeda | — | Speaker | Applications in ML Drug Discovery pipelines | Video |
| Fabio Buso | Hopsworks | Speaker | How to build a serverless electricity price prediction service in just Python with Hopsworks and Streamlit | Video |
| Fabio Pliger | — | Speaker | PyScript & Data Science- PyData stack on the Browser | Video |
| Han Wang | Lyft | Speaker | Testing Big Data Applications (Spark, Dask, and Ray) | Video |
| Hemant Jain | Cohere | Speaker | Large Language Models for Real-World Applications - A Gentle Intro | Video |
| Iain Campbell | — | Speaker | A Graph-based Machine Learning early warning system to detect Ransomware | Video |
| Ilinca Barsan | — | Speaker | A Guide to Data Science as a Creative Discipline | Video |
| Isaac Godfried | — | Speaker | Deep learning for time series forecasting and classification in practice | Video |
| Isabel Zimmerman | — | Speaker | Holistic MLOps for better science | Video |
| James Powell | Don't Use This Code | Speaker | Why do I need to know Python? I'm a pandas user… | Video |
| Jamie DeMaria | — | Tutorial | Troubleshooting your Data Workflows with Noteable + Dagster: A live debugging of failed jobs. | Video |
| Jeff Hale | Prefect | Speaker | Supercharge your Python code with Blocks | Video |
| Jeff Reback | — | Speaker | pandas at a Crossroads, the Past, Present, and Future | Video |
| Joe Cheng | Posit | Speaker | Shiny for Python: Interactive apps and dashboards made easy-ish | Video |
| Jon Wiggins | — | Speaker | Understanding the News around the World with Web Scraping and NLP at Scale | Video |
| Joshua E. Jodesty | — | Speaker | CATs: Content-Addressable Transformers | Video |
| Juan Luis | Orchest | Speaker | Expressive and fast dataframes in Python with polars | Video |
| Jules S. Damji | — | Tutorial | Distributed Python with Ray: Hands on with the Ray 2.0 APIs for scaling Python Workloads | Video |
| Kei Nemoto | — | Speaker | Gentle introduction to scaling up ML service with Kubernetes + Mlflow | Video |
| Kevin Kho | — | Tutorial | Fast and Scalable Timeseries Modelling with Fugue and Nixtla | — |
| Kjell Wooding | — | Speaker | Zeno Does Data Science- The Paradoxical Quest for Reproducibility | Video |
| Kshetrajna Raghavan | Shopify | Speaker | Using Interconnected ML Models to Tackle Retail Challenges | Video |
| Lara Kattan | — | Speaker | Simulations in Python: Discrete Event Simulation with SimPy | Video |
| Lauren Oldja | — | Speaker | NumFOCUS Champions Circle presents- How to make friends and generate impact | Video |
| Lawrence Wilson Gray | KPMG | Speaker | 20 ideas to build social capital in the Data Science ecosystem | Video |
| Martin Hirzel | — | Speaker | Fairness for Scikit-Learn Pipelines with Lale | Video |
| Martin Shell | Avaiga | Speaker | Turning Data/AI algorithms into production-ready applications in no time with Taipy, the next-gen Python application builder | — |
| Matthew Rocklin | — | Speaker | Deploying Dask | Video |
| Max Mergenthaler | Nixtla | Speaker | NixtlaVerse, bridging the gap between statistics and deep learning for time series. | Video |
| Melissa McNeill | University of Chicago Crime Lab | Speaker | Customizable probabilistic record linkage with Name Match | Video |
| Moussa Taifi | Xandr | Speaker | ML Latency No More: Useful Patterns to Reduce ML Prediction Latency to Sub X ms | Video |
| Nidhin Pattaniyil | — | Speaker | Serving Pytorch Models in Production | Video |
| Peter Vidos | Vizzu | Tutorial | ipyvizzu-story - a new, open-source tool to build, create and share animated data stories with Python in Jupyter | Video |
| Piero Ferrante | — | Speaker | Coldstart- A library for automatic data curation + feature engineering | Video |
| Pierre Brunelle | Noteable | Tutorial | Troubleshooting your Data Workflows with Noteable + Dagster: A live debugging of failed jobs. | Video |
| Popescu Daniel | — | Speaker | Prompt Engineering ⚙️ - Addressing the sensitivity of Large language models | Video |
| Robert Alvarez | — | Speaker | Hands-On Computer Vision with PyTorch | Video |
| Rohit Supekar | The New York Times | Speaker | Causal machine learning for a smart paywall at The New York Times | Video |
| Roni Kobrosly | — | Speaker | Introduction to Causal Inference | Video |
| Sanjay Siddhanti | — | Speaker | Implementing a Workflow Engine in Python | Video |
| Savin Goyal | Outerbounds | Speaker | Human-Friendly, Production-Ready Data Science Stack with Metaflow & Kubernetes | Video |
| Sophia Yang | — | Speaker | Level up your viz skills- from Matplotlib to HoloViz | Video |
| Thomas J. Fan | Quansight | Speaker | Parallelism in Numerical Python Libraries | Video |
| Tonya Sims | — | Speaker | Discover Inspirational Insights in Motivational Sports Speeches Using Speech-to-Text | Video |
| Zach Musgrave | — | Speaker | Git for Data: Data Versioning for Reproducible Data Science with Dolt | Video |