Conference Schedule

View past PyData event schedules here.

Tutorial Sessions — Wednesday July 5, 2017

  Track 1 - Hood Track 2 - Baker Track 3 - Rainier Track 4 - St. Helens
9:00 AM

Breakfast & Registration

10:00 AM Using CNTK's Python Interface for Deep Learning Dave DeBarr D’oh! Unevenly spaced time series analysis of The Simpsons in Pandas Joe McCarthy From Novice to Data Ninja Valentina Staneva So you want to be a Python expert? James Powell
12:00 PM

Lunch

1:00 PM Introduction to data analytics with pandas Quentin Caudron Parallelizing Scientific Python with Dask Jim Crist, David Mertz pomegranate: fast and flexible probabilistic modeling in python Maxwell W Libbrecht Effective Visual Studio Steve Dower
3:00 PM

Break/Snacks

3:20 PM Data Visualization and Exploration with Python Stephen Elston A Quick Primer on TensorFrames: Apache Spark and TensorFlow Together Denny Lee, Tomasz Drabas Python Web Sraping Lingqiang Kong Vocabulary Analysis of Job Descriptions Alex Thomas
5:20 PM

General Sessions — Thursday July 6, 2017

  Track 1 - McKinley Track 2 - Kodiak Track 3 - Hood Track 4 - Rainier
8:00 AM

Breakfast & Registration

9:00 AM Keynote (McKinley & Livestream in Cascade) Katrina Riehl
10:00 AM Scalable Data Science in Python and R on Apache Spark Felix Cheung Using Scattertext and the Python NLP Ecosystem for Text Visualization Jason Kessler Provenance for Reproducible Data Science Andreas Schreiber Monitoring Displacement Crises with Python: A Humanitarian Project by Data for Democracy George Richardson
10:45 AM Designing for Guidance in Machine Learning Olivia Gunton Automatic Citation generation with Natural Language Processing Claire Kelley, Sarah Kelley Practical Optimization for Stats Nerds Ryan J. O'Neil PixieDust - make Jupyter Python Notebooks with Apache Spark Faster, Flexible, and Easier to use Raj Singh
11:30 AM Pandas, Pipelines, and Custom Transformers Julie Michelman Scan Statistics with Spark Streaming: Distribution Based Real Time Anomaly Detection Michal Monselise National Geospatial-Intelligence Agency: Changing the Bureaucrat’s Mind Toward Data-Driven Decisions Gary Dunow Unlocking the power of AI: A fundamentally different approach to building intelligent systems Keen Browne
12:15 PM

Lunch

1:05 PM Keynote (McKinley & Livestream in Cascade) Jake Vanderplas
2:05 PM Robust Automated Forecasting in Python and R Pranav Bahl, Jonathan Stacks In-database Machine Learning with Python in SQL Server - Sponsor Talk Sumit Kumar How to be a 10x Data Scientist Stephanie Kim Code First, Math Later: Learning Neural Nets Through Implementation and Examples Kyle Shaffer
2:50 PM Python and IoT: From Chips and Bits to Data Science Jeff Fischer Applying the four-step "Embed, Encode, Attend, Predict" framework to predict document similarity Sujit Pal WorldRowing.com: End To End Data Analysis Lou Harwood How diversity drives excellence in our data-driven tech world PyData Seattle Diversity Panel
3:35 PM

Break/Snacks

3:50 PM Big data processing with Apache Beam Sourabh Bajaj Make it Work, Make it Right, Make it Fast - Debugging and Profiling in Dask Jim Crist Python for .NET or .NET for Python Denis Akhiyarov, Xavier Dupré Moving notebooks into the cloud: challenges and lessons learned Saranga Komanduri, Lori Eich
4:35 PM Chatbots - Past, Present and Future Dr. Rutu Mulkar-Mehta Of Mice & Python: Building a Brain Observatory for Visual Behavior Justin Kiggins, Doug Ollerenshaw Batch and Streaming Processing in the World of Data Engineering and Data Science Keira Zhou Forecasting Time Series Data at scale with the TICK stack Nathaniel Cook
5:20 PM PyData "Pub" Quiz! (Kodiak) Moderated by James Powell
6:05 PM

Social Event

8:05 PM

General Sessions — Friday July 7, 2017

  Track 1 - McKinley Track 2 - Kodiak Track 3 - Hood Track 4 - Rainier
8:00 AM

Breakfast & Registration

9:00 AM Keynote (McKinley & Livestream in Cascade) Joseph Sirosh
10:00 AM Sirbarksalot: Bark Detection in Python Nicholas Kridler Mosaicking the Earth every day Kelsey Jordahl High Fidelity Web Crawling in Python Josh Weissbock Medical image processing using Microsoft Deep Learning framework (CNTK) Naoto Usuyama, Jessica Lundin
10:45 AM Building a community fountain around your data stream Maria Patterson High-Performance Distributed Tensorflow: Request Batching and Model Post-Processing Optimizations Chris Fregly Implementing and Training Predictive Customer Lifetime Value Models in Python Jean-Rene Gauthier, Ben Van Dyke Learn to be a painter using Neural Style Painting Pramit Choudhary
11:30 AM bqplot - Interactive Data Visualization in Jupyter Dhruv Madeka Making packages and packaging "just work" Michael Sarahan Beginning Julia: Language and Landscape en zyme Scaling Scikit-Learn Stephen Hoover
12:15 PM

Lunch

1:05 PM Interactive Data Analysis: Visualization and Beyond (McKinley & Livestream in Cascade) Jeffrey Heer
2:05 PM JupyterLab+Real Time Collaboration Brian Granger, Chris Colbert & Ian Rose We came, we saw, we hacked. How to win a Big Data hackathon Eloisa Tran Bokeh and Friends Bryan Van de ven Machine Learning Infrastructure at Stripe: Bridging from Python -> JVM Rob Story
2:50 PM

Break/Snacks

3:05 PM BrainDrain: Using Machine Learning and Brain Waves to Detect Errors in Human Problem Solving Katie Porterfield Writing a Book in Jupyter Notebooks Randall J. LeVeque Upgrading Legacy Projects: Lessons Learned Matt Braymer-Hayes, Erin Haswell Robust Algorithms for Machine Learning Tom Radcliffe
4:00 PM

Lightning Talks

5:00 PM

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