Conference Schedule

View past PyData event schedules here.

Tutorial Sessions — Friday May 5, 2017

  Auditorium LG6 LG7 Dining Room
10:00

Registration

10:25 Make your research interactive with Jupyter Dashboards Pavlo Andriychenko

Room in use

Topic Modelling (and more) with NLP framework Gensim Lev Konstantinovskiy From zero to Kung Fu Panda(s) Jonathan Fernandes
12:00

Break and snacks

12:15 Introduction to Convolutional Neural Networks using TensorFlow and Keras Oliver Zeigermann

Room in use

Building a ChatBot with Python, NLTK and scikit Edward Bullen Jupyter Notebooks for geospatial data analysis Julia Wagemann, Stephan Siemen
13:50

Lunch (Atrium)

14:35 Twisted up in a Distributed Tornado - a beginners guide to async frameworks in python Andrew Stretton Tutorial One workshop that data scientists don't want you to attend... Oliver Laslett, Andraz Hribernik Test-Driven Data Analysis Nick Radcliffe
16:10

Break and snacks

16:25 Easy Bayesian regularization for fitting financial time series and curves Dr. Egor Kraev Ten Steps to Keras Valerio Maggio Seeing the invisible - Bayesian Mixture Models Elena Nemtseva Building Web-based Analysis & Simulation Platforms with React/Redux, Flask, Celery, Bokeh, and Numpy James Powell
18:00

General Sessions — Saturday May 6, 2017

  Auditorium LG6 LG7 Dining Room
8:00

Registration and breakfast

9:00 KEYNOTE: Automated factchecking in the era of fake news Will Moy, Mevan Babakar
10:00 Bayesian optimisation with scikit-learn Thomas Huijskens Static Type Analysis for Robust Data Products Marco Bonzanini Machine Learning in Financial Credit Risk Assessment Soledad Galli Scale out from the very beginning Jens Nie
10:45

Breaks and snacks

11:00 Variational Inference and Python Peadar Coyle High-Performance Distributed Tensorflow: Request Batching and Model Post-Processing Optimizations Chris Fregly Using Random Forests in Python Nathan Epstein A beginner's guide to data analysis in cosmology using Jupyter Notebook Dr Caroline Clark
11:45 Pythonic Polling Analysis and Comments on 2016's Polling Surprises Aileen Nielsen ❤ Analyzing the ElectroCardioGram (ECG) and classifying what's healthy and what's not. Dr. Emlyn Clay Yellowbrick: Steering Machine Learning with Visual Transformers Rebecca Bilbro

Making your first open-source contribution
Demo and hands on session!

12:30

Lunch

13:30 KEYNOTE: Picasso's terminal; data science and AI in the visual arts Gene Kogan
14:30 Diversity and Data: Cases in the Music Industry Delger Enkhbayar, Mike Sumner How distributed representations make chatbots work (at least a bit) Nils Hammerla Machine learning with ventilator data to improve reporting on critically ill newborn infants Ian Ozsvald, Dr Gusztav Belteki, Giles Weaver

Full Fact Hackathon

15:15

Breaks and snacks

16:15 Julia: A Fresh Approach to Machine Learning Mike Innes A laser light show on a quantum scale Tiffany Harte Journeys through JuPyteR Alex Glaser

Full Fact Hackathon

17:00 SaaaS - Sampling as an Algorithm Service Vincent D. Warmerdam Show me the failures! Data products for manufacturing at shop floor Thomas Alisi To explain or to predict? Nick Sorros

Full Fact Hackathon

17:45

⚡ Lightning talks ⚡

18:30

After-party at Finch's

23:59

General Sessions — Sunday May 7, 2017

  Auditorium LG6 LG7 Dining Room
8:00

Registration and breakfast

9:00 KEYNOTE: Data for good: Lessons from the frontline Emma Deraze, Charlie Harrison
10:00 Recommender systems with Tensorflow Guillaume Allain Efficient and portable DataFrame storage with Apache Parquet Uwe L. Korn Is having dementia linked to where you live? Frank Kelly, Ondrej Urban Extracting Insight From A Muslim Marriage App Laila Alabidi
10:45

Break and snacks

11:00 Bayesian Deep Learning with Edward (and a trick using Dropout) Andrew Rowan Segmenting Channel 4 Viewers using LDA Topic Modelling Thomas Nuttall "Lights, camera, AI!" - Automated sports videography Zack Akil Astrophysics to data Science: how the Milky Way is like my company. Kathryn Harris
11:45 Ranking hotel images using deep learning Nuno Castro Find the text similiarity you need with next generation of word embeddings in Gensim Lev Konstantinovskiy Outlier detection methods for detecting cheaters in mobile gaming Andrew Patterson

Unconference

12:30

Lunch

13:30 WTF am I doing? An introduction to NLP and ANN's Jeff Abrahamson Analyzing 3D objects with power of Deep Learning and Cython Alexandr Notchenko Building robust machine learning systems Stephen Whitworth

Gensim sprint
Lev Konstantinovskiy

14:15 Smart search using Support vector machines Dr. Shahzia Holtom Leveraging recommender systems to personalise search results Soraya Hausl Smelly London: visualising historical smells through text-mining, geo-referencing and mapping. Deborah Leem, Barbara McGillivray

Gensim sprint
Lev Konstantinovskiy

15:00 An Algorithm of Style Ed Snelson Interactively Analyse 100GB of Data using Spark, Amazon EMR and Zeppelin Raoul-Gabriel Urma, Valentin Dalibard Finding the Right Articles - A Supervised Approach to Search Yasen Kiprov, Pepa Gencheva

Gensim sprint
Lev Konstantinovskiy

15:45

Break and snacks

16:00 Forecasting social inequality using agent-based modelling James Allen Computational challenges of genome assembly, and how to beat them. Katie Barr Dimension Reduction and Extracting Topics - A Gentle Introduction Tariq Rashid

Probabilistic Models
Vincent Warmerdam

16:45

⚡ Lightning talks ⚡

17:45