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