Conference Schedule

View past PyData event schedules here.

Tutorial Sessions — Friday July 12, 2019

	Tower Suite 1	Tower Suite 2	Tower Suite 3
8:00	Registration
9:00	Build and Deploy an End-to-end Streaming NLP Insights System Michal Mucha	Maintainable Code in Data Science Kevin Lemagnen	Data Analysis in Parallel Filip Ter
10:30	Break & Snacks
11:00	A Deep Dive into NLP with PyTorch Jeffrey Hsu, Susannah Klanecek	Advanced Software Testing for Data Scientists Raoul-Gabriel Urma, Kevin Lemagnen	Mastering Gradient Boosting with CatBoost Anna Veronika Dorogush
12:30	Lunch
13:30	Choosing the right neural generative model for your problem Dr Egor Kraev	Fundamentals of image classification using PyTorch Jonathan Fernandes	An Introduction to Markov chain Monte Carlo using PyMC3 Chris Fonnesbeck
15:00	Break & Snacks
15:30	Training intelligent game agents using deep reinforcement learning Imran Rashid	AB-testing by clusters Bertil Hatt, João Martins	A gentle introduction to Pandas timeseries and Seaborn Ian Ozsvald
17:00

General Sessions — Saturday July 13, 2019

	Tower Suite 1	Tower Suite 2	Tower Suite 3	Mortimer Room
8:00	Registration
9:00	Opening Notes
9:15	The Turing Way: A how to guide for reproducible research Kirstie Whitaker
10:00	Break & Snacks
10:15	A practical guide towards algorithmic bias and explainability in machine learning Alejandro Saucedo	Data Science for Dinner: Recommending Recipes Irene Iriarte Carretero	Modelling the subsurface with gamma rays and machine learning Connor Tann	Unconference
11:00	Because You Can Run, You Can't Hide: Some Musings on API Design James Powell	I am telling you 3 things about Chatbot (so you don't have to learn it the hard way) Cheuk Ting Ho	Active learning in the interactive python environment Jan Freyberg	Unconference
11:45	How am I going to deal with all of these cats? Liam Kirwin	Embeddings! Embeddings everywhere! - How to build a recommender system using representation learning Maciej Arciuch, Karol Grzegorczyk	Testing and Validating Machine Learning Models when Deploying to Production Christopher Samiullah, Soledad Galli	Executives at PyData Ian Ozsvald, James Powell
12:30	Lunch (Diversity Lunch in the lunch seating area, the Carvery)
13:30	You got served: How Deliveroo improved the ranking of restaurants Jonny Brooks-Bartlett	Productionising Data Science at Scale Trevor Sidery, Guillermo Barquero	On the Path to Causal Inference Mark Farragher	Democracy Hackathon John Sandall, Richard Chadwick
14:15	Prophet at Scale: Using Prophet at scale to tune and forecast time series at Spotify Mahan Hosseinzadeh	What Failure Taught Me About Building High-Stakes Models That Actually Work Jake Coltman,	Understanding exchange network dynamics with Python Omer Yuksel
15:00	Modern Data Science: A new approach to DataFrames and pipelines Maarten Breddels, Jovan Veljanoski	Image search without image captions Harrison Pim	How to Validate Your Client Churn Model Elena Sharova
15:45	Break & Snacks
16:00	Bridging health inequalities through machine learning Elina Naydenova
16:45	Lightning Talks & Closing Notes
17:45	PyData Social Reception and Pub Quiz (Exhibition foyer)
21:00

General Sessions — Sunday July 14, 2019

	Tower Suite 1	Tower Suite 2	Tower Suite 3	Mortimer Room
8:00	Registration
9:00	Opening Notes
9:15	Goofing Off with Fun (Big) Data Lynn Cherny
10:00	Break & Snacks
10:15	Combining Computer Vision and NLP for Multi-Task Fashion Attribute Modeling at Shoprunner Michael Sugimura	Quantamental Investing - the future of finance Fabian Krause	Interpretable AI or How I Learned to Stop Worrying and Trust AI Ajay Thampi,	Text annotation role playing workshop (Interactive workshop for unconference) Lev Konstantinovskiy, Agata Sumowska, Bhargav Srinivasa Desikan, Michał Łopuszyński, w4rner
11:00	The unreasonable effectiveness of feature hashing Gianluca Campanella	A Primer (or Refresher) On Linear Algebra for Data Science Ruben van de Geer	Understanding of distributed processing in Python Chie Hayashida	How to make your first open source contribution Cheuk Ting Ho
11:45	Kafka in Finance: processing >1 Billion market data messages a day Matthew Hertz, Alla Maher	How to Constrain Artificial Stupidity. Vincent Warmerdam	Weak supervision: a new paradigm for unreliable labels Eddie Bell	How to make Python Packages Michal Mazurek and Igor Gotibovych
12:30	Lunch (PyData Organisers Lunch in the lunch seating area, the Carvery)
13:30	Safer Cycling with an Edge TPU watching your back Zack Akil	Data science and Internet of Things on the edge Mario Bonamigo	Just ask: designing intent-driven algos Anna Schneider	Facilitated discussion on practical implementation of ethical data science Anthony Woolcock
14:15	Data Science Frameworks and Managed Services: When to Avoid the Shiny New Toys Jon Tutcher	From healthcare.hospital import datascience Pavlos Papaconstadopoulos, Patrick Gonzalez	Knowledge graphs --enter--> the Hype Cycle George Cushen	Chatbots that know if you are angry Cheuk Ting Ho
15:00	Deep Learning and Time Series Forecasting for Smarter Energy Igor Gotlibovych	The anatomy of a #deepfake Eric Drass aka shardcore	How good is your prediction? - Quantifying uncertainty in Machine Learning predictions Maria Navarro	Unconference
15:45	Break & Snacks
16:00	One step forward, two steps back: the frustration of diversity efforts in STEM Lorena A. Barba
16:45	Lightning Talks & Closing Notes
18:00

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