Predictive modelling with Python (keynote) (Olivier Grisel)
https://www.youtube.com/watch?v=Ll6qWDbRTD0
http://ogrisel.github.io/decks/2016_pydata_berlin/
https://github.com/ogrisel/docker-distributed
Python Data Ecosystem: Thoughts on Building for the Future (Wes McKinney)
https://www.youtube.com/watch?v=iL98TfFlUD8
http://de.slideshare.net/wesm/python-data-ecosystem-thoughts-on-building-for-the-future
What's new in Deep Learning? (Kashif Rasul)
https://www.youtube.com/watch?v=mw-NfRO1jv0
https://www.dropbox.com/s/b6lgvq6ijlutii4/new-deep-learning.pdf?dl=0
Classifying Search Queries Without User Click Data (Abhishek Thakur)
https://www.youtube.com/watch?v=6e12EMglzTs
Dealing with TBytes of Data in Realtime (Nils Magnus)
https://www.youtube.com/watch?v=Xjk2GWVpH-g
One in a billion: finding matching images in very large corpora (Ryan Henderson)
https://www.youtube.com/watch?v=DfWLBzArzKE
https://github.com/ascribe/image-match
Machine Learning at Scale (Nathan Epstein)
https://www.youtube.com/watch?v=nn8ZvJb07QI
What every data scientist should know about data anonymization (Katharina Rasch)
https://www.youtube.com/watch?v=O3hxp117EHs
https://github.com/krasch/presentations/blob/master/pydata_Berlin_2016.pdf
Accelerating Python Analytics by In-Database Processing (Edouard Fouché)
https://www.youtube.com/watch?v=J9kbKhzuMd0
https://ibmdbanalytics.github.io/pydata-berlin-2016-ibmdbpy.slides.html
Holy D@t! How to Deal with Imperfect, Unclean Datasets* (Katharine Jarmul)
https://www.youtube.com/watch?v=QRdLn-QccWk
https://docs.google.com/presentation/d/1G-lgHKTdrqeeJhcvVmd7C9gOIfTRe429zhBN6lmKKzA/
Designing spaCy: Industrial-strength NLP (Matthew Honnibal)
https://www.youtube.com/watch?v=gJJQs47aUQ0
pypet: A Python Toolkit for Simulations and Numerical Experiments (Robert Meyer)
https://www.youtube.com/watch?v=a8Qq8kPS-dg
http://pypet.readthedocs.org/
PySpark in Practice (Ronert Obst, Dat Tran)
https://www.youtube.com/watch?v=ZojIGRS3HLY
Zero-Administration Data Pipelines using AWS Simple Workflow (Anne Matthies)
https://www.youtube.com/watch?v=RiONy5W9Afk
Visualizing research data: Challenges of combining different datasources (Juha Suomalainen)
https://www.youtube.com/watch?v=qB9DbNAFUJQ
Plumbing in Python: Pipelines for Data Science Applications (Thomas Reineking)
https://www.youtube.com/watch?v=R1em4C0oXo8
Bayesian Optimization and it's application to Neural Networks (Moritz Neeb)
https://www.youtube.com/watch?v=0sG8zHK_VA4
Brand recognition in real-life photos (Lukasz Czarnecki)
https://www.youtube.com/watch?v=0Ho0O1tvcU4
http://de.slideshare.net/ukaszCzarnecki/brand-recognition-in-reallife-photos-using-deep-learning-lukasz-czarnecki-pydata-berlin-2016/
Usable A/B testing – A Bayesian approach (Nora Neumann)
https://www.youtube.com/watch?v=PSqtcNZDj4A
https://speakerdeck.com/nneu/b-testing-a-bayesian-approach
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