Conference Schedule

View past PyData event schedules here.

🌴 icons represent local speakers.

Tutorial Sessions β€” Sunday Oct. 21, 2018

  Fertitta Hall, Room LL105 Fertitta Hall, Room LL125 Popovich Hall, Room 110
8:00 AM

Breakfast & Registration

9:00 AM Learning to Scale Data Science, Machine Learning, and Pandas with Ray and Modin Devin Petersohn When Rotten Tomatoes Isn’t Enough: Analyzing Twitter Movie Reviews Using DataStax Enterprise Amanda K Moran Introduction to Data Manipulation and Visualizations in R David Sung 🌴
10:30 AM

Break

11:00 AM Network Science, Game of Thrones and US Airports Mridul Seth A Hands-On Application of Causal Methods in Python Abi Aryan 🌴 Tips, Tricks and Topics in Text Analysis Bhargav Srinivasa Desikan
12:30 PM

Lunch

1:30 PM Docker for Data Science: Reproducibility and Deployment Hareem Naveed Applying Statistical Modeling and Machine Learning to Perform Time-Series Forecasting Tamara Louie Testing with Pytest for Data Science Ravin Kumar 🌴
3:00 PM

Coffee Break

3:30 PM CatBoost - The New Generation of Gradient Boosting Vasily Ershov An Introduction to Julia Jane Herriman 🌴 Making Computation Easier with Cool Numpy Tricks Kirit Thadaka
5:00 PM

General Sessions β€” Monday Oct. 22, 2018

  The Trojan Ballroom / ML The Franklin Suite, 3rd Floor / Technical The Forum, 4th Floor / NLP
8:00 AM

Breakfast & Registration

9:00 AM

Opening Notes

9:15 AM Keynote #1: Building a Player-Focused Data Team at Riot Games Andrea Trevino 🌴
10:00 AM

Break

10:15 AM Time, Interrupted: Measuring Intervention Effects with Interrupted Time-Series Analysis Ben Cohen Serverless for Data Scientists Mike Lee Williams 🌴 Data Mining JIRA Tickets to Gain Insights into Organizational Behavior Wendy Grus
11:00 AM

Break

11:15 AM 1D Convolutional Neural Networks for Time Series Modeling Nathan Janos 🌴, Jeff Roach Developing Dashboard Applications Using Bokeh Bryan Van de Ven Why You Should Do Text Analysis in Python (Even if You Don't Want to) Bhargav Srinivasa Desikan
12:00 PM

Lunch

1:00 PM (Deep) Learn You a Neural Net for Great Good! Stu (Michael Stewart) JupyterLab: The Evolution of the Jupyter Notebook Ian Rose 🌴, Grant Nestor Accelerating Data Science with RAPIDS Mike Wendt
1:45 PM

Break

2:00 PM Hot Water Leak Detection Using Variational Autoencoder Model Jay Kim 🌴 Iodide and Pyodide: Bringing Data Science Computation to the Web Browser Michael Droettboom, Brendan Colloran, Hamilton Ulmer Extracting Structured Data from Legal Documents Zack Witten
2:45 PM

Coffee & Sponsor Break

3:15 PM Attacking Clustered Data with a Mixed Effects Random Forests Model in Python Sourav Dey Help! I Just Inherited 50,000 Lines of Code! What Do I Do? β€” A Practical Guide James Powell Detecting Signed and Unsigned Documents with Deep Learning - Beyond Transfer Learning Jordan Bramble
4:00 PM

Break

4:15 PM Keynote #2 - Tensorly: A Flexible Python Framework for Machine Learning Anima Anandkumar 🌴
5:00 PM

Lightning Talks

5:45 PM

General Sessions β€” Tuesday Oct. 23, 2018

  The Trojan Ballroom / ML The Franklin Suite, 3rd Floor / Technical The Forum, 4th Floor / Case Studies
8:00 AM

Breakfast & Registration

9:00 AM

Opening Notes

9:15 AM Building an Open Platform for Sustaining Data Science Innovation: A Tour of NumFOCUS Projects Andy Terrel
10:00 AM

Break

10:15 AM Measuring Model Fairness Stephen Hoover StaticFrame: An Immutable Alternative to Pandas Christopher Ariza 🌴 Python at City Scale Hunter Owens 🌴
11:00 AM

Break

11:15 AM Customer Lifetime Value: Models, Metrics and a Multitude of Uses Brian Bloniarz What's the Science in Data Science? Skipper Seabold Building a Visualizer in Yellowbrick Nathan Danielsen 🌴
12:00 PM

Lunch

1:00 PM Big Problems at the Heart of Machine Learning Abi Aryan 🌴 Deploy and Use a Multiframework Distributed Deep Learning Platform on Kubernetes ANIMESH SINGH, Tommy Li Using Data to Get Your Next Raise Michelle Brenner 🌴
1:45 PM

Break

2:00 PM Using Simpson’s Paradox to Discover Interesting Patterns in Behavioral Data Nazanin Alipourfard 🌴, Peter Fennell Extending Pandas with Custom Types Will Ayd 🌴 Train, Evaluate, Repeat: Building a Credit Card Fraud Detection System Leela Senthil Nathan
2:45 PM

Coffee Break

2:55 PM

Lightning Talks

3:15 PM Keynote #4: What is a Data Desk? Ben Welsh 🌴
4:00 PM

Break

4:10 PM Keynote #5: The New Science of Cause and Effect Judea Pearl 🌴
4:55 PM

Closing Notes

5:05 PM

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