Conference Schedule

View past PyData event schedules here.

Tutorial Sessions — Friday Oct. 7, 2016

  Room #370B/C (3rd Floor) Room #220/219 (2nd Floor) Room #1023/1022/1020 (1st Floor)
8:00 AM

Breakfast & Registration
9:00 AM Using Dask for Parallel Computing in Python Skipper Seabold How to Build Your Own Self-Driving (Toy) Car Ryan Zotti Pandas from the Inside Stephen Simmons
10:30 AM

Break
10:45 AM Parallel Python - Analyzing Large Data Sets Aron Ahmadia, Matthew Rocklin Beyond Sentiment -- Emotion Mining with Python and machine learning Max Tsvetovat Educational framework for Black Box optimization methods design with scikitlearn and scipy Nadia Udler
12:15 PM

Lunch
1:00 PM Modern NLP in Python Patrick Harrison Building Your First Data Pipelines Hunter Owens Doing frequentist statistics with Scipy Gustavo A. Patino
2:30 PM

Break
2:45 PM Machine Learning with Text in scikit-learn Kevin Markham Interactive multi-scale time series exploration with matplotlib Thomas Caswell The Five Kinds of Python Functions Steven Lott
4:15 PM Learn how to Make Life Easier with Anaconda Dhavide Aruliah Getting started with H2O on Python Ashrith Barthur Julia Tutorial Chase Coleman
5:45 PM

General Sessions — Saturday Oct. 8, 2016

  Room #370B/C (3rd Floor) Room #1025 (1st Floor) Room #1023/1022/1020 (1st Floor) Room #220/219 (2nd Floor)
8:00 AM

Breakfast & Registration
9:00 AM

Opening Notes
9:15 AM Building a Data-Driven Dialogue: From Filling Potholes to Disrupting the Cycle of Incarceration Kelly Jin
10:00 AM Keynote: How Open Data Science Opens the World of Innovation Robert Cohn, Peter Wang
10:45 AM

Break
11:00 AM JupyterLab: Building Blocks for Interactive Computing Jason Grout Creating Python Data Pipelines in the Cloud Femi Anthony Bayesian Network Modeling using R and Python Pragyansmita Nayak Scaling up to Big Data - Devops for Data Science Marck Vaisman
11:45 AM How I learned to time travel, or, data pipelining and scheduling with Airflow Laura Lorenz Fuzzy Search Algorithms: How and When to Use Them Jiaqi Liu Beyond Bag of Words: A Practitioner’s Guide to Advanced NLP Using Open Source Ariel M’ndange-Pfupfu, Mike Anderson A Practical Guide to Dimensionality Reduction Techniques Vishal Patel
12:30 PM

Lunch in Atrium

Diversity Luncheon with Rebecca Bilbro- Difference, Discomfort and Disruption: My first year in open source (Rm #2008/2006)
1:30 PM Keynote: Become a Data Superhero: How Data Can Change the World Elizabeth Lindsey
2:15 PM Building Serverless Machine Learning Models in the Cloud Alex Casalboni Forecasting critical food violations at restaurants using open data Nicole Donnelly Eat Your Vegetables - Data Security for Data Scientists Will Voorhees Agent-based modeling in Python Jackie Kazil
3:00 PM NoSQL doesn't mean No Schema Steven Lott Creating a Contemporary Lending Risk Management System Using Python Piero Ferrante Clustering: A Guide for the Perplexed Leland McInnes, John Healy From rocks to a hammer: when and how to change your company's analytical tools Sebastien Genty
3:45 PM

Break
4:00 PM Python useRs Daniel Chen Promoting a data-driven culture in a world of microservices Alex DeBrie, Kelly Burdine Data Sciencing While Female Mandi Traud H2O PySparkling Water Michal Malohlava
4:45 PM Building Continuous Learning Systems Anuj Gupta Predicting Usage for Capital Bikeshare stations based upon Spatial Characteristics Darshan Pandit Variational Inference in Python Austin Rochford Building a (semi) Autonomous Drone with Python Greg Lamp
5:30 PM

General Sessions — Sunday Oct. 9, 2016

  Room #370B/C (3rd Floor) Room #1025 (1st Floor) Room #1023/1022/1020 (1st Floor) Room #220/219 (2nd Floor)
8:00 AM

Breakfast & Registration
9:00 AM Keynote: The Culture of Data Transformation SriSatish Ambati
9:45 AM Keynote: Extending from Open to Usable: A Commerce Data Conundrum Star Ying
10:30 AM

Break
10:45 AM Making your code faster: Cython and parallel processing in the Jupyter Notebook Gustavo A. Patino Triaging Feedback Form Data  Stephanie Kim Machine Learning Techniques for Class Imbalances & Adversaries Brendan Herger ElasticSearch and Redis: How and When to Use Them Tim Marcinowski
11:30 AM Dask for ad-hoc distributed computing Matthew Rocklin You got your engineering in my Data Science: Addressing the reproducibility crisis with Software Eng Jon Bodner Data Transformation: A Framework for Exploratory Data Analysis Tony Ojeda Becoming a Data Scientist: Advice From My Podcast Guests Renee M. P. Teate
12:15 PM

Lunch in Atrium

Fireside Chat/Panel with Star Ying and Pri Oberoi
1:15 PM Improving PySpark Performance: Spark performance beyond the JVM Holden Karau Open Data Dashboards & Python Web Scraping Marie Whittaker Dynamics in Graph Analysis: Adding Time as a Structure for Visual and Statistical Insight Benjamin Bengfort Design Principles James Powell
2:00 PM Logistic Regression: Behind the Scenes Christopher D. White Sustainable scrapers David Eads Dev Ops meets Data Science: Taking models from prototype to production with Docker and Kubernetes Andy Terrel Bot or Not? The Illusion of Intelligence Bobby Filar
2:45 PM

Break
3:00 PM GraphGen: Conducting Graph Analytics over Relational Databases Konstantinos Xirogiannopoulos H2O Deep Water with Python early sneek Fabrizio Milo Visual diagnostics for more informed machine learning Rebecca Bilbro Exposing Algorithms Jennifer A. Stark
3:45 PM

Lightning Talks
4:30 PM

Closing Notes & Door Prizes
4:45 PM