Conference Schedule

View past PyData event schedules here.

	Room 1	Room 2
8:00 AM	Breakfast & Registration
9:00 AM	Learning scikit-learn -- An Introduction to Machine Learning in Python Sebastian Raschka	Pandas: .head() to .tail() Tom Augspurger
10:30 AM	Break
10:45 AM	pomegranate: fast and flexible probabilistic models in python Jacob Schreiber	Building a Recommendation Engine with Neo4j and Python Kevin Van Gundy
12:15 PM	Lunch
1:15 PM	Luigi & Data Pipelines Hunter Owens	A Quickstart Guide to PyMC3 Nicole Carlson
2:45 PM	Break
3:00 PM	Intro to Julia Huda Nassar	Popping Kernels: An Exploration of Kernel Development for Jupyter Notebooks Safia Abdalla
3:45 PM	Intro to Julia Huda Nassar	Using Dask for Parallel Computing in Python Skipper Seabold
5:15 PM

	Room 1	Room 2
8:00 AM	Breakfast & Registration
9:00 AM	Opening Notes
9:15 AM	Keynote Katy Huff
10:00 AM	Forecasting with the Kalman Filter Mike Mull	Deconstructing Feather Bill Lattner
10:45 AM	Break
11:00 AM	Adding Image and Voice Intelligence to Your Apps with Microsoft Cognitive Services David Giard	Don't Live Patch Your CPython Interpreter James Powell
11:45 AM	It's Not Magic: Explaining Classification Algorithms Brian Lange	Mind the Gap! Bridging the pandas – scikit-learn dtype divide Tom Augspurger
12:30 PM	Lunch
1:30 PM	Keynote: Using Data Science for Social Good: Examples, Opportunities, and Challenges Rayid Ghani
2:15 PM	Fizz Buzz in Tensorflow Joel Grus	Data Engineering Architecture at Simple Rob Story
3:00 PM	Break
3:15 PM	Pyglmnet: A Python package for elastic-net regularized generalized linear models Pavan Ramkumar	High Frequency Trading in MMORPG Markets using Luigi, Pandas, and Scikit-learn J. Henry Hinnefeld
4:00 PM	Deploying Machine Learning using sklearn pipelines Kevin Goetsch	What Data Analysts Wish Application Developers Knew Alison Stanton
4:45 PM	Lightning Talks
5:30 PM

	Room 1	Room 2
8:00 AM	Breakfast & Registration
9:00 AM	Keynote: Developing Communities to Develop Themselves Matthew Turk
9:45 AM	Implementing distributed grid search for deep learning using scikit-learn and joblib Mike Heilman	Embracing the Monolith in Small Teams: Doubling down on python to move fast without breaking things. Leon Sasson
10:30 AM	Break
10:45 AM	Finding Driving-Style Patterns in Caterpillar Machine Data Benjamin Hodel	Creating a Contemporary Risk Management System Using Python Piero Ferrante
11:30 AM	Python Framework for Zero-shot Learning Approach: An Application on Network Intrusion Detection. Jorge Luis Rivero Pérez	A Year of Pyxley: My First Open-Source Adventure Nicholas Kridler
12:15 PM	Lunch
1:15 PM	Keynote: Builtin Superheroes David Beazley
2:00 PM	When Worlds Collide: Productionalizing a Data Science Model Tudor Radoaca, Nicole Carlson	AutoDocish: Automated-ish Dataset Documentation Elizabeth Wickes
2:45 PM	Using Exploratory Data Analysis to Discover Patterns in Image and Document Collections Mehrdad Yazdani	Create Spark REST APIs with flask Michael David Watson
3:30 PM	Break
3:45 PM	Genotype-Phenotype Modelling with Python and Machine Learning Mat Kallada	Using Twitter's Breakout Detection Package Eric Bunch
4:30 PM	Evolutionary Algorithms: Perfecting the Art of "Good Enough" Liz Sander	Machine learning techniques for data cleaning Cathy Deng
5:15 PM	Closing Notes & Door Prizes
5:30 PM