Conferences / PyData
PyData Los Angeles 2019
Dec 3–5, 2019 · California State University, Los Angeles (Golden Eagle Ballroom), Los Angeles, CA, United States
- Conference
- PyData Data science & ML
- Dates
- Dec 3, 2019 – Dec 5, 2019
- Venue
- California State University, Los Angeles (Golden Eagle Ballroom)
- Place
- Los Angeles, CA, United States
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- pydata.org
- Recorded
- 9 sponsors · 50 speaker appearances
- Notes
- Dec 3 was tutorials plus open-source sprints; Dec 4-5 talks. Speakers: keynotes from the keynotes page plus all scheduled talks/tutorials; affiliations only where the pydata.org speaker profile states one. Video URLs matched from the PyData YouTube playlist "PyData LA 2019". Prices from the Eventbrite listing (no early-bird dates shown); a free Sprinter pass was also offered. The CatBoost talk listed under Anna Veronika Dorogush was recorded with Vasily Ershov presenting (https://www.youtube.com/playlist?list=PLGVZCDnMOq0pHVE3SB0ecki__VMncQPKo).
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Student Tutorials Pass (Tue only) | $75 | — | eventbrite.com | |
| Individual Tutorials Pass (Tue only) | $150 | — | eventbrite.com | |
| Student Talk Pass (Wed & Thu only) | $200 | — | eventbrite.com | |
| Corporate/Start-up Tutorials Pass (Tue only) | $200 | — | eventbrite.com | |
| Individual Talk Pass (Wed & Thu only) | $250 | — | eventbrite.com | |
| Student 3-Day Pass | $275 | — | eventbrite.com | |
| Startup Talk Pass (Wed & Thu only) | $300 | — | eventbrite.com | |
| Individual 3-Day Pass | $400 | — | eventbrite.com | |
| Corporate Talk Pass (Wed & Thu only) | $400 | — | eventbrite.com | |
| Startup 3-Day Pass | $500 | — | eventbrite.com | |
| Corporate 3-Day Pass | $600 | — | eventbrite.com |
Sponsors 9
Bronze 1
Other 1
- Win-Vector LLC · Supporting
Speakers and talks 50
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Carol Willing | — | Keynote | Start Small and Scale: Big Data and Jupyter's Ecosystem | Video |
| Kyle Polich | Data Skeptic Labs | Keynote | Python in the Stream, the Lake, and on the Edge | Video |
| Milana Lewis | Stem | Keynote | Clarity over Transparency | Video |
| Sameer Singh | University of California, Irvine | Keynote | — | Video |
| Adrien Treuille | Streamlit | Speaker | Turn Python Scripts into Beautiful ML Tools | Video |
| Amanda Moran | Databricks | Speaker | To Production and Beyond: How to Manage the Machine Learning Lifecycle with MLflow | — |
| Amy Tzu-Yu Chen | System1 | Speaker | What's Data Science Reporting? | Video |
| Ana Castro Salazar | H2O.ai | Speaker | Introduction to Data Analysis with Python datatable | Video |
| Anna Veronika Dorogush | — | Speaker | Gradient Boosting for data with both numerical and text features | — |
| Avik Das | Speaker | Dynamic programming for machine learning: Hidden Markov Models | Video | |
| Ben Fowler | Southeast Toyota Finance | Speaker | Evaluation of Traditional and Novel Feature Selection Approaches | Video |
| Brad Rees | NVIDIA | Speaker | RAPIDS: Open Source GPU Data Science | Video |
| Christopher Ariza | Research Affiliates | Speaker | Fitting Many Dimensions into One: The Promise of Hierarchical Indices for Data Beyond Two Dimensions | Video |
| Daniel J. Brooks | Toyota/Aioi Insurance | Speaker | Computer Vision with PyTorch | Video |
| Dante Gama Dessavre | NVIDIA | Speaker | Open Source is Better Together: GPU Python Libraries Unite | Video |
| Dmitry Petrov | Iterative | Speaker | Datasets and machine learning models versioning using open source tools | Video |
| Eric Busboom | Civic Knowledge | Speaker | Tackling Homelessness with Open Data | Video |
| Fletcher Riehl | System1 | Speaker | Modeling Search Term Revenue: Using Embedding Layers to Manage High Cardinality Categorical Data | Video |
| Franklin Sarkett | — | Speaker | Building a Data Driven Organization | Video |
| Franklin Velasquez | H2O.ai | Speaker | Introduction to H2O AutoML with Python | Video |
| Hao Jin | Amazon Web Services | Speaker | Accelerate your NumPy Data Science Workloads and Deep Learning Applications | Video |
| Hareem Naveed | Munich Re | Speaker | Write the Docs! | Video |
| Hayley Song | University of Washington | Speaker | Experimental Machine Learning with HoloViz and PyTorch in Jupyterlab | Video |
| Ivona Tautkute | — | Speaker | AI meets Fashion for product retrieval with multi-modally generated data | Video |
| James Powell | — | Speaker | What You Got Is What You Got | Video |
| Jeffrey Mew | Microsoft | Speaker | Build an AI-powered Pet Detector in Visual Studio Code | Video |
| John Healy | Tutte Institute for Mathematics and Computing | Speaker | MAP all the things | Video |
| John Mount | Win-Vector LLC | Speaker | Preparing messy data for supervised learning with vtreat | Video |
| Joseph Kearney | Millennium Management | Speaker | Introducing Autoimpute: a Python Package for Grappling with Missing Data | Video |
| Juan S Vasquez | — | Speaker | Web Scraping w BeautifulSoup & Yelp's API | Video |
| Kevin Chrzanowski | — | Speaker | Bokeh Maps: Making an interactive map for your next web application | Video |
| Leland McInnes | Tutte Institute for Mathematics and Computing | Speaker | Learning Topology: Topological Techniques for Unsupervised Learning | Video |
| Malte Loller-Andersen | Knowit | Speaker | Reinforcement Learning: Pac-Man | Video |
| Manu Flores | Caltech | Speaker | Analyzing genetic networks using neural networks | Video |
| Manu Gopinathan | Knowit | Speaker | Reinforcement Learning: Pac-Man | Video |
| Maria Khalusova | JetBrains | Speaker | Machine Learning Model Evaluation Metrics | Video |
| Matthew Seal | Netflix | Speaker | Data and ETL with Notebooks in Papermill | Video |
| Michelle Brenner | — | Speaker | Ahead in the Clouds: How to get started with serverless on Google, Amazon & Microsoft | Video |
| Nick Acosta | IBM | Speaker | IBM Code and Response: Open Sourcing Natural Disaster Preparedness and Relief | Video |
| Nina Zumel | Win-Vector LLC | Speaker | Preparing messy data for supervised learning with vtreat | Video |
| Pasha Stetsenko | — | Speaker | Introduction to Data Analysis with Python datatable | Video |
| Paul Anzel | H-E-B | Speaker | Git-ting along with others | Video |
| Raul Maldonado | Autodesk | Speaker | A/B Testing in Python | Video |
| Ravin Kumar | Sweetgreen | Speaker | Making data relevant to business. Its harder than you think! | Video |
| Richard Liaw | UC Berkeley | Speaker | A Guide to Modern Hyperparameter Tuning Algorithms | Video |
| Rodolfo Bonnin | Mercado Libre | Speaker | A "Supremely" Light introduction to Quantum Computing | Video |
| Shahid Barkat | Cisco | Speaker | Introducing Autoimpute: a Python Package for Grappling with Missing Data | Video |
| Sujit Pal | Elsevier | Speaker | Building Named Entity Recognition Models Efficiently using NERDS | Video |
| Tim Orme | Ancestry | Speaker | Simplicity For Scale: Analyzing 15 Million DNA Samples With Python | Video |
| Tom Goldenberg | QuantumBlack | Speaker | Kedro + MLflow – Reproducible and versioned data pipelines at scale | Video |
Sources
- https://pydata.org/la2019/
- https://pydata.org/la2019/schedule/
- https://pydata.org/la2019/sponsors/
- https://pydata.org/la2019/venue/
- https://pydata.org/la2019/pydata-la-2019-keynotes/
- https://www.eventbrite.com/e/pydata-la-2019-tickets-66383126719
- https://www.youtube.com/playlist?list=PLGVZCDnMOq0pHVE3SB0ecki__VMncQPKo