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 How to be fair: a tutorial for beginners Aileen Nielsen 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 Putting Tensorflow Models into Production Bugra Akyildiz
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

Keynote 1

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 TBA 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
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
12:30

Lunch

13:30 You got served: How Deliveroo improved the ranking of restaurants Jonny Brooks-Bartlett TBD Trevor Sidery On the Path to Causal Inference Mark Farragher

Unconference

14:15 Prophet at Scale: Using Prophet at scale to tune and forecast time series at Spotify Mahan Hosseinzadeh Making sense of messy geo data Tom Putnam, 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

Keynote 2

16:45

Lightning Talks & Closing Notes

17:45

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

Keynote 3

10:00

Break & Snacks

10:15 Large Scale Graph Mining with Spark: What I learned from mapping >15 million websites Win Suen Quantamental Investing - the future of finance Fabian Krause Interpretable AI or How I Learned to Stop Worrying and Trust AI Ajay Thampi,

Unconference

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
11:45 Kafka in Finance: processing >1 Billion market data messages a day Matthew Hertz How to Constrain Artificial Stupidity. Vincent Warmerdam Weak supervision: a new paradigm for unreliable labels Eddie Bell
12:30

Lunch

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

Unconference

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
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
15:45

Break & Snacks

16:00

Keynote 4

16:45

Lightning Talks & Closing Notes

18:00

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