Conference Schedule

View past PyData event schedules here.

Tutorial Sessions — Friday July 6, 2018

  Track 2 Track 1
8:00

Registration & Breakfast

9:00 Tricks, tips and topics in Text Analysis Bhargav Srinivasa Desikan Using GANs to improve generalization in a semi-supervised setting - trying it in open datasets Andreas Merentitis, Carmine Paolino, Vaibhav Singh
10:30

Break

10:45 Leveling up your storytelling and visualization skills Gerrit Gruben Deep Neural Networks with PyTorch Stefan Otte
12:15

Lunch

13:15 A Hands-On Introduction to Your First Data Science Project Em Grasmeder, Jin Yang Scaling and reproducing deep learning on Kubernetes with Polyaxon Mourad Mourafiq
14:45

Coffee

15:00 Search Relevance: A/B testing to Reinforcement Learning Arnab Dutta Production ready Data-Science with Python and Luigi Mark Keinhörster
16:30

Break

16:45 Deprecating the state machine: building conversational AI with the Rasa stack Justina Petraitytė Deploying a machine learning model to the cloud using AWS Lambda Dr. Benjamin Weigel
18:15

General Sessions — Saturday July 7, 2018

  Audimax Hörsaal 3 Kursraum 1 Kursraum 3
8:30

Registration & Breakfast

9:30

Opening Notes

9:45 Keynote: Hacking the Iron Curtain: From smuggling computer parts to owning the world Andrada Fiscutean
10:45

Break

11:00

Neural Networks

NLP & Text Analysis

Python Applications

Tools of the Trade

11:00 Visual concept learning from few images Vaibhav Singh ML and populism Limor Gultchin Five things I learned from turning research papers into industry prototypes Ellen König

Q&A with Keynote Andrada Fiscutean

11:45 Simple diagrams of convoluted neural networks Dr. Piotr Migdał Where NLP and psychology meet Alexandra Klochko Spatial Data Analysis With Python Dillon R. Gardner, PhD Towards automating machine learning: benchmarking tools for hyperparameter tuning Dr. Thorben Jensen
12:30 Deep Neural Networks for Double Dummy at Bridge Lorand Dali ctparse: a practical parser for natural language time expressions in pure python Dr. Sebastian Mika Python Unittesting for Ethereum Smart Contracts or how not to create your own Cryptocurrency Robert Meyer Launch Jupyter to the Cloud: an example of using Docker and Terraform Cheuk Ting Ho
13:15

Lunch

14:15

Algorithms

NLP & RNNs

Python in the Field

Unsupervised Learning & Visualization

14:15 Let's SQL Like It's 1992! James Powell Building new NLP solutions with spaCy and Prodigy Matthew Honnibal Python in Medicine: analysing data from mechanical ventilators and patient monitors Gusztav Belteki Manifold Learning and Dimensionality Reduction for Data Visualization and Feature Engineering Stefan Kühn
15:00 A/B testing at Zalando: concepts and tools Shan Huang, Grigory Bordyugov How I Made My Computer Write it's First Short Story Alexander Hendorf How to scare a fish (school) Andrej Warkentin Extracting relevant Metrics with Spectral Clustering Evelyn Trautmann
15:45 Solving very simple substitution ciphers algorithmically Stephen Enright-Ward Understanding and Applying Self-Attention for NLP Ivan Bilan AI in Healthcare David Higgins On Laplacian Eigenmaps for Dimensionality Reduction Juan Orduz
16:30

Coffee

16:45 Keynote: Building in Privacy and Data Protection -- what is demanded by the GDPR? Marit Hansen
17:45

Lightning Talks

Q&A with Keynote Marit Hansen

18:45

Social event @ Lindengarten Wedding — FREE DRINKS! (and "PyData Pub Quiz" with James Powell, Matti Lyra, Elad Verbin)

23:00

General Sessions — Sunday July 8, 2018

  Audimax Hörsaal 3 Kursraum 1 Kursraum 3
8:00

Registration & Breakfast

9:00 Keynote - Fairness and Diversity in Online Social Systems Elisa Celis
10:00

Break

10:15

ML in Production

Explainability and Privacy

Computer Vision & CNNs

 

10:15 Industrial ML - Overview of the technologies available to build scalable machine learning Alejandro Saucedo GDPR in practise - Developing models with transparency and privacy in mind Łukasz Mokrzycki When to go deep in Computer Vision... and how Irina Vidal Migallón

Q&A with Keynote Elisa Celis

11:00 How mobile.de brings Data Science to Production for a Personalized Web Experience Dr. Florian Wilhelm, Dr. Markus Schüler Privacy-preserving Data Sharing Omar Ali Fdal Object detection to Instance segmentation: Learn to apply several algorithms along the way Sujatha Subramanian Surviving Interviews with Media (unrecorded) Andrada Fiscutean
11:45 Simplifying Training Deep & Serving Learning Models with Big Data in Python using Tensorflow Holden Karau pyGAM: balancing interpretability and predictive power using Generalized Additive Models in Python Dani Servén Marín The Face of Nanomaterials: Insightful Classification Using Deep Learning Angelo Ziletti Making your first open source contribution James Powell, Adrin Jalali, Matti Lyra
12:30

Lunch

13:30

Best Practices

Extending Python

Bayesian Methods

13:30 Going Full Stack with Data Science: Using Technical Readiness Level to Guide Data Science Outcomes Emily Gorcenski Career Panel Hosted by Nakeema Stefflbauer (followed by Q&A) Nakeema Stefflbauer Interfacing R and Python Andrew Collier All that likelihood with PyMC3 Junpeng Lao
14:15 Data versioning in machine learning projects Dmitry Petrov Extending Pandas using Apache Arrow and Numba Uwe L. Korn Modern Approaches to Bayesian Learning with Neural Networks Paul J. Rozdeba
15:00

Coffee

15:15

Performance

New Libraries

Visualization Tools

 

15:15 Big Data Systems Performance: The Little Shop of Horrors Jens Dittrich CatBoost: Fast Open-Source Gradient Boosting Library For GPU Vasily Ershov Meaningful histogramming with Physt Jan Pipek Software Development Core Skills: `git` James Powell, Valentina Scipione
16:00 Battle-hardened advice on efficient data loading for deep learning on videos. Valentin Haenel LightFields.jl: Fast 3D image reconstruction for VR applications Hector Andrade Loarca Practical examples of interactive visualizations in JupyterLab with Pixi.js and Jupyter Widgets Jeremy Tuloup
16:45

Lightning Talks & Closing Notes

17:30

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