Conference Schedule

View past PyData event schedules here.

Tutorial Sessions — Friday Aug. 12, 2016

	Theater	Speakeasy	Boardroom
8:00 AM	Breakfast & Registration
9:00 AM	TrailDB tutorial: Store and process billions of events efficiently Ville Tuulos	What's new in Python 3 James Powell	--
10:30 AM	Break
10:45 AM	Pandas, Data Wrangling & Data Science Krishna Sankar	Building Recommender Systems using Python Divya Sardana	--
12:15 PM	Lunch
1:15 PM	Build Data Apps by Deploying ML Models as API Services Ramesh Sampath	Python Visualization for Exploration of Data Stephen F. Elston, Ronald Lopez	Overview of the NumFOCUS Data Science Stack James Powell
2:45 PM	Break
3:00 PM	Data Applications with Bokeh Bryan Van de Ven	Applied Time Series Econometrics in Python (and R) Jeffrey Yau	Introduction to Julia Tony Kelman
5:15 PM

General Sessions — Saturday Aug. 13, 2016

	Theater	Speakeasy	Boardroom
8:00 AM	Breakfast & Registration
9:00 AM	Opening Notes
9:15 AM	Keynote: Empowering people by democratizing data skills Tracy Teal
10:00 AM	JupyterLab Jamie Whitacre	Closing the Machine Learning Loop using Python Randall Shane, PhD	Building domain specific databases using Python for prototypes during take-off Josh Yudaken
10:45 AM	Break
11:00 AM	Community sustainability in Wikipedia: a review of research and initiatives Stuart Geiger	Searchable datasets in Python: images across domains, experiments, algorithms and learning Dani Ushizima, Flavio Araujo, Romuere Silva	Time Series for Python with PyFlux Ross Taylor
11:45 AM	The "NumPy" Approach James Powell	A Practical Introduction to Airflow Matt Davis	Nipype: a framework for developing efficient and reliable medical imaging data analysis pipelines Chris Gorgolewski
12:30 PM	Lunch
1:30 PM	TBD Peter Wang
2:15 PM	Moving Forward Through The Darkness Chia-Chi Chang	Machine Learning vs. The Flu: Creating better Flu Vaccines with Python and Machine Learning Rohan Koodli	Fighting Against Chaotically Separated Values with Embulk Sadayuki Furuhashi
3:00 PM	Break
3:15 PM	Large Scale CTR Prediction - Lessons Learned Florian Hartl	How Soon is Now: automatically extracting publication dates of news articles with machine learning Julie Lavoie	BoF -
4:00 PM	Resampling techniques and other strategies for handling highly unbalanced datasets in classification Ajinkya More	Transfer Learning and Finetuning Deep Convolution Neural Network on different domain-specific images Anusua Trivedi	BoF -
4:45 PM	Lightning Talks
5:30 PM

General Sessions — Sunday Aug. 14, 2016

	Theater	Speakeasy	Boardroom
8:00 AM	Breakfast & Registration
9:00 AM	Keynote: Using the Python Data Science Stack to Determine How Many People Have Been Killed in Syria Megan Price
9:45 AM	Anaconda Ecosystem for Open Data Science Ian Stokes-Rees	Derivation & Presentation: How to Effectively Tell A Data Science Story In A Business Environment Gregory Kamradt	How to Scrape Data from any Website Greg Dingle
10:30 AM	Break
10:45 AM	Clustering Data Science Interviews: Seven Related but Distinct Categories Samantha Zeitlin	Prescriptive Analytics with DOcplex and pandas Veronique Blanchard	Carousel - A Python Model Simulation Framework Mark Mikofski
11:30 AM	Virtual Laboratories: Vision for an Earth Sciences Collaborative And Distributed Environment Charles Doutriaux	Why is Windows so broken? (and what to do about it) Steve Dower	A hybrid approach to model randomness and fuzziness using Dempster-Shaffer method. Taposh Roy, Austin Powell
12:15 PM	Lunch
1:15 PM	Keynote: Working Efficiently with Big Data in Text Formats David Mertz, Ph.D.
2:00 PM	Creating Knowledgebases from unstructured text. Sanghamitra Deb	Mental Models to Use and Avoid as a Data Scientist Jonathan Whitmore, Christian Perez	BoF -
2:45 PM	Altair: Declarative, Statistical Visualization for Python Brian E. Granger	Similarity Search in Patents via modern Artificial Intelligence Sumeet Sandhu, Tami Lee	BoF -
3:30 PM	Break
3:45 PM	Visualizing Geographic Data With Python Christopher Roach	Applying machine learning to software development to reduce bugs Nitin Borwankar	BoF -
4:30 PM	How you really get your data science models into production - the cool way! Dat Tran	Architectures for Exploring Your Personal Data Candida Haynes	BoF -
5:15 PM	Closing Notes & Door Prizes
5:30 PM