Conference Schedule

View past PyData event schedules here.

Tutorial Sessions — Friday April 27, 2018

  Tower Suite 1 Tower Suite 2 Tower Suite 3
8:00

Registration
9:00 Automatic tagging of short texts with scikit-learn and NLTK Gilbert François Duivesteijn Computer Vision: An (Un?)Expected Journey, with Keras and Tensorflow Rodolfo Bonnin Test-Driven Data Analysis Nick Radcliffe
10:30

Break & Snacks
11:00 Apache Airflow in the Cloud: Programmatically orchestrating workloads with Python Satyasheel, Kaxil Naik Build text classification models ( CBOW and Skip-gram) with FastText in Python Kajal Puri, Sandeep Saurabh Deep Probabilistic Methods with PyTorch Chris Ormandy
12:30

Lunch
13:30 Anomaly Detection Nick Radcliffe Making computation easier with cool Numpy tricks Kirit Thadaka Network Science, Game of Thrones and US Airports Mridul Seth
15:00

Break & Snacks
15:30 Understanding and diagnosing your machine-learning models Gaël Varoquaux Hypothesis Testing with SciPy Hillary Green-Lerman Follow the gradient: an introduction to mathematical optimisation Gianluca Campanella
17:00

General Sessions — Saturday April 28, 2018

  Tower Suite 1 Tower Suite 2 Tower Suite 3 Mortimer Room
8:00

Registration
9:00 Democratising data journalism: building a collaborative and investigative network across the UK Charles Boutaud
10:00

Break & Snacks
10:15 Sentence embeddings for automated factchecking Lev Konstantinovskiy CatBoost - the new generation of gradient boosting Anna Veronika Dorogush Data, Science: Investigating 1 Million Galaxies with Humans and TensorFlow Mike Walmsley

Unconference: Make your first open-source contribution
11:00 Python Doesn’t Have to Be Slow: Speeding Up a Large-Scale Optimization Algorithm Dat Nguyen Why giving your algorithm ALL THE FEATURES does not always work. Thomas Huijskens Touchdown Localisation with aircraft flight data Jonathan G. Pelham

Unconference
11:45 Beyond word2vec: GloVe, fastText, StarSpace. Konstantinos Perifanos Creating correct and capable classifiers Ian Ozsvald Demystifying pandas internals Marc Garcia

Unconference
12:30

Lunch & Algorithmic Art Expo
13:30 Evaluating fairness in machine learning with PyMC3 Oliver Laslett A Data Science Approach to Systemic Risk Nikolai Nowaczyk Building out data science at QBE Liam P. Kirwin

Algorithmic Art Hackathon
14:15 Stationary data? Forget about it! Bayesian forgetting and Random Effects for forecasting TV ratings Ruadhán Stokes Emphasising Relationships in the BBC's Data Using Technologies of the Semantic Web Theo Windebank More About Generators James Powell
15:00 Winning with Simple, even Linear, Models Vincent D. Warmerdam A/B Testing with Style Alistair Lynn Python at Massive Scale Stephen Simmons, Neil Slinger
15:45

Break & Snacks
16:00 Making the Big Data ecosystem work together with Python: Apache Arrow, Spark, Beam, and Dask Holden Karau
16:45

Lightning Talks & Closing Notes
17:30

General Sessions — Sunday April 29, 2018

  Tower Suite 1 Tower Suite 2 Tower Suite 3 Mortimer Room
8:00

Registration
9:00 Learning programming and science with Scientific Python Emmanuelle Gouillart
10:00

Break & Snacks
10:15 Auto-encoders in the wild... of telco land. Guillermo Christen Multi-touch Attribution: What am I training for ? Sri Sri Perangur RNN sequence labeling for document parsing in Tensorflow Carsten van Weelden

Pandas Sprint
11:00 JupyterHub from the Ground Up with Kubernetes Camilla Montonen Searching for Shady Patterns: Shining a light on UK corporate ownership Adam Hill Unsupervised Anomaly Detection with Isolation Forest Elena Sharova
11:45 Databases for Data Science Alex Hendorf Data Deduplication using Locality Sensitive Hashing Matti Lyra Reliably forecasting time-series in real-time Charles Masson
12:30

Lunch & Diversity Round Table
13:30 Be good (and don't be evil): how to audit your work for fairness and inclusion Aileen Nielsen Visualising NLP pipelines with Pynorama Slavi Marinov Do tyres dream of electric clouds? Tom Alisi Politics Hackathon John Sandall, Frank Kelly
14:15 How will the new EU data protection laws affect your work? Will Hardy Using Survival Analysis to understand customer retention Lorna Brightmore Big Data Oceanography James Munroe
15:00 Who's singing? Automatic bird sound recognition with machine learning Dan Stowell Data Science in Energy - Adding a new facade to an old asset. Prashant Tiwari Planes, Trains, and Skateboard Shoes - Bayesian methods in engineering and product design Jim Parr
15:45

Break & Snacks
16:00 Artistic Applications of Artificial Intelligence Luba Elliott
16:45

Lightning Talks & Closing Notes
17:30

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