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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