Conference Schedule

View past PyData event schedules here.

Keynotes Talks Tutorials

Tutorial Sessions — Friday May 6, 2016

	Auditorium	LG6	LG7	Dining
10:00	Registration/Breakfast
10:25	Lies damned lies and statistics in Python Peadar Coyle		Bokeh for Data Applications and Visualization Bryan Van de Ven	Beginner Bootcamp Conrad Ho
11:00	Lies damned lies and statistics in Python Peadar Coyle	Pandas from the inside Stephen Simmons		Beginner Bootcamp Conrad Ho
12:00	Break and Snacks
12:15	Building a Pong playing AI in just 1 hour(plus 4 days training...) Daniel K Slater	Python and Julia: the best of friends? Malcolm Sherrington	Open Work Space	Beginners' Bootcamp (continued) Conrad Ho
13:50	Lunch (Atrium)
14:35	Deep learning tutorial - advanced techniques Geoffrey French, Calvin Giles	Building a recommendation engine with Python and Neo4j Mark Needham	JupyterHub: Deploying Jupyter Notebooks for students and researchers Min Ragan-Kelley, Kyle Kelley, Thomas Kluyver	Open Work Space
16:10	Break and Snacks (Atrium)
16:25	Introduction to Deep Learning & Natural Language Processing Raghotham Sripadraj, Nischal HP	Using Python with Hadoop to create production ready big data applications Ulrich Zink	Bayesianism and Survival Analysis Jake Coltman, Jacob Goodwin	Open Work Space
18:00

General Sessions — Saturday May 7, 2016

	Auditorium	LG6	LG7	Dining
8:00	Registration/Breakfast
9:00	KEYNOTE: Laser ranging in a new dimension Andreas Freise
10:00	Building Data Pipelines in Python Marco Bonzanini	To the Web and Beyond Kyran Dale	AlzHack: Data Driven Diagnosis of Alzheimer's Disease Frank Kelly, Giles Weaver	Classifying train and car journeys using telematics data Annabelle Rolland
10:45	Break and Snacks
11:00	Interactive Visualization in Jupyter with Bqplot and Interactive Widgets Sylvain Corlay	A/B Testing: Harder than just a color change Or Weizman	Statistically Solving Sneezes and Sniffles (Step by Step) Ian Ozsvald, Giles Weaver	The NetworkL python package Moreno Bonaventura
11:45	PySpark in Practice Ronert Obst, Dat Tran	Survival Analysis in Python and R Linda Uruchurtu	Using Support Vector Machines in Scikit-Learn to discover genetic aetiologies in Schizophrenia Tim Vivian-Griffiths	Iterables and Iterators: Going Loopy With Python Steve Holden
12:30	Lunch
13:30	How to become a Data Scientist in 6 months: a hacker’s approach to career planning Tetiana Ivanova
14:30	The Duct Tape of Heroes: Bayesian statistics. Vincent D. Warmerdam	Lessons from 6 months of using Luigi in production Pete Owlett	Challenges of analysing the wheat genome Katie Barr	Open Work Space
15:15	Break and Snacks
15:30	Estimating stock price correlations using Wikipedia Delia Rusu	10 things I learned about writing data pipelines in Python and Spark. Ali Zaidi	Python vs Orangutan Dirk Gorissen	Unconference Presentation
16:15	Real-time association mining in large social networks Ben Chamberlain	Cat modelling with python John Gill	Mining smartphone sensor data with python Neal Lathia	Unconference Presentation
17:00	Making Recommendations without Data Ruby Childs, Nick Sorros	The CV: A Data Scientist's View Rui Miguel Forte	Python and Johnny Cash James Powell	Unconference Presentation
17:45
18:30	We are Wizards after-party at Bierschenke
23:59

General Sessions — Sunday May 8, 2016

	Auditorium (LYST DEEP LEARNING)	LG6	LG7	Dining
8:00	Registration/Breakfast
9:00	KEYNOTE: Scaling Out PyData Travis Oliphant
10:00	A Gentle Introduction to Neural Networks (and making your own with Python) Tariq Rashid	Assessing the quality of a clustering Christian Hennig	DyND: Enabling complex analytics across the language barrier Irwin Zaid	bandicoot: a toolbox to analyze mobile phone metadata Luc Rocher
10:45	Break and Snacks
11:00	Working with Fashion Models Eddie Bell	Probabilistic Programming in Python with PyMC3 Thomas Wiecki	Cross-modal Representation Learning Tanmoy Mukherjee, Maryam Abdollahyan	Estimating Residential Land Prices in the UK Philippe Bracke
11:45	Finding needles in haystacks with Deep Neural Networks Calvin Giles	Hierarchical Bayesian Modelling with PyMC3 and PySTAN Jonathan Sedar	Twinkle twinkle little star, how I wonder what you are... Sandra Greiss	Unconference Presentation
12:30	Lunch
13:30	Deep Learning for QSAR Rich Lewis	Julia for Data Analysis: features, interfaces and future directions Simon Byrne	Detecting novel anomalies in Twitter Delia Rusu, Mattia Boni Sforza	Python flying at 40,000 feet Marko Vasiljevski, Raffaele Rainone
14:15	Irregular time series and how to whip them Aileen Nielsen	What's new in High Performance Python? Graham Markall	Word Embeddings for fun and profit in Gensim Lev Konstantinovskiy	Unconference Presentation
15:00	Modelling a text corpus using Deep Boltzmann Machines in python Ricardo Pio Monti	Robot detection in IT environments Eszter Windhager-Pokol	Spherical Voronoi Diagrams in Python Nikolai Nowaczyk	Unconference Presentation
15:45	Break and Snacks
16:00	Assurance Scoring: Using Machine Learning and Analytics to Reduce Risk in the Public Sector Natalia Angarita-Jaimes, Matt Thomson	Customising nbconvert: how to turn Jupyter notebooks into anything you want Thomas Kluyver, Min Ragan-Kelley	Gotta catch'em all: recognizing sloppy work in crowdsourcing tasks Maciej Gryka	Unconference Presentation
16:45	Lightning Talks
17:45