Talks

Slides or presentation material for the talks are currently being collected and are published as soon as we get them.

All the videos are available as a YouTube collection.

If you don’t want to use YouTube, you can download the MP4 files from here.

Keynote

• Python for non-coders
  By: David Louapre, Science étonnante & Ubisoft
  Slides: David Louapre-629a77af.pdf
  Video: here

• Technical Debt: the Code Monster in your Closet
  By: Nina Zakharenko, Microsoft
  Slides: Nina Zakharenko-3b99e364.pdf
  Video: here

Core Python

• Crossing the native code frontier
  By: Serge sans Paille, Namek
  Slides / presentation material (online): http://serge-sans-paille.github.io/talks/pydata2018/output/index.html#/step-1
  Video: here

• DSL in Pyrser
  By: Lionel Auroux, LSE EPITA
  Slides: Lionel Auroux-5d4ebb18.pdf
  Video: here

• How to use AsyncIO to make the most of a CPU Bound and IO Bound software with Python 3.7
  By: Rémy Hubscher, ChefClub
  Slides / presentation material (online): https://natim.github.io/django-slides/asyncio-io-cpu-bound-en/#/
  Video: here

• Porting application from Python 2.x to 3.x
  By: Philippe Boulanger, INVIVOO
  Slides: Philippe Boulanger-6d79b508.pdf
  Video: here

• Unexpected Dataclasses
  By: Pierre Alexandre Schembri, NETSACH
  Slides: Pierre Alexandre Schembri-9cc74f5a.pdf
  Video: here

• Using type annotation in Python
  By: Philippe Fremy, IDEMIA
  Slides: Philippe Fremy-31b0239a.pdf
  Video: here

Data Science

• (Deep) Machine Learned Model Deployment with ONNX
  By: Xavier Dupré, Microsoft
  Slides / presentation material (online): http://www.xavierdupre.fr/app/jupytalk/helpsphinx/notebooks/onnx_deploy_pyparis.html#onnxdeploypyparisrst
  Video: here

• A Short History of Array-based Computing in Python
  By: Wolf Vollprecht, QuantStack
  Slides: Wolf Vollprecht-0cc86b66.pdf
  Video: here

• Beat a Google Ads Bidder using ML
  By: Arnaud Fouchet, Dolead
  Slides: Arnaud Fouchet-87114fa3.pdf
  Video: here

• Data Science for Industry 4.0
  By: Alessandro Giassi, Saint-Gobain Recherche Paris
  Slides: Alessandro Giassi-f1044c5f.pdf
  Video: here

• Deep Learning with PyTorch for more Fun and Profit (Part 2.5)
  By: Alexander Hendorf, KÖNIGSWEG
  Slides: Alexander Hendorf-7570ac42.pdf
  Video: here

• Exploring image processing pipelines with scikit-image, joblib, ipywidgets and dash
  By: Emmanuelle Gouillart, Joint Unit CNRS / Saint-Gobain
  Slides: Emmanuelle Gouillart-59486166.pdf
  Video: here

• GeoAlchemy: using SQLAlchemy with Spatial databases
  By: Éric Lemoine, Oslandia
  Slides: Éric Lemoine-52b7f92c.pdf
  Video: here

• Geospatial data processing for image automatic analysis
  By: Raphaël Delhome, Oslandia
  Slides: Raphaël Delhome-2d4267d1.pdf
  Video: here

• Let the AI Do the Talk: Adventures with Natural Language Generation
  By: Marco Bonzanini, Bonzanini Consulting Ltd
  Slides: Marco Bonzanini-a80fa109.pdf
  Video: here

• Machine Learning with Scikit-Learn: quick clusterization of a very large malware dataset
  By: Robert Erra, EPITA
  Slides: Robert Erra-99ad525c.pdf
  Video: here

• Modern Pandas - Writing effective, readable data pipeline
  By: Hervé Mignot, Equancy
  Slides: Hervé Mignot-2c465b89.pdf
  Slides / presentation material (online): https://github.com/HerveMignot/PyParis2018
  Video: here

• Pyodide: scientific Python compiled in WebAssembly, and application
  By: Roman Yurchak,
  Slides / presentation material (online): https://rth.github.io/talks/PyParis2018/#1
  

• Robosat: an Open Source and efficient Semantic Segmentation Toolbox for Aerial Imagery
  By: Olivier Courtin, DataPink
  Slides: Olivier Courtin-486f7730.pdf
  Video: here

• Scikit-learn: news on making even better machine learning
  By: Gael Varoquaux, Inria & Tom Dupré la Tour, Telecom Paristech
  Slides: Gael Varoquaux+Tom Dupré la Tour-493b61d1.pdf Gael Varoquaux+Tom Dupré la Tour-a9c79f34.pdf
  Video: here

• *Segmentation of 3-D materials science images : from raw data to physical measurements *
  By: Chloe Brillatz, CNRS/St Gobain Research Paris
  Slides: Chloe Brillatz-34877355.pdf
  Video: here

• Using Deep Learning to rank and tag millions of hotel images
  By: Christopher Lennan, idealo.de & Tanuj Jain, Idealo
  Slides: Christopher Lennan+Tanuj Jain-475f1087.pdf
  Video: here

• Vaex: Out of Core Dataframes for Python
  By: Maarten Breddels, Independant / Maarten Breddels & Jovan Veljanoski, XebiaLabs
  Slides: Maarten Breddels+Jovan Veljanoski-a00dc422.pdf
  Slides / presentation material (online): https://github.com/maartenbreddels/talk-pyparis-2018
  Video: here

Tools

• Interactive widgets in the Jupyter Notebook
  By: Martin Renou, QuantStack
  Slides: Martin Renou-ad2c3fca.pdf
  Slides / presentation material (online): https://github.com/QuantStack/quantstack-talks/tree/master/2018-11-14-PyParis-widgets
  Video: here

• Jupytext: Edit Jupyter notebooks represented as Python scripts
  By: Marc Wouts, Capital Fund Management
  Slides / presentation material (online): https://github.com/mwouts/jupytext_pyparis_2018/blob/master/README.md
  Video: here

• Version control in 2018: present and future
  By: Pierre-Yves David, Octobus.net
  Slides / presentation material (online): https://octobus.net/presentations/version-control-2018.html#/title-slide
  

• Vim Your Python, Python Your Vim
  By: Miroslav Šedivý, UBIMET GmbH
  Slides: Miroslav Šedivý-a6df38f3.pdf
  Video: here

Web & Cloud

• A better way to use modern Javascript/Node.js with Django
  By: Romain Dorgueil, Makersquad
  Slides: Romain Dorgueil-a3f47138.pdf
  Video: here

• *Anyblok WMS Base *
  By: Georges Racinet, Anybox SAS
  Slides / presentation material (online): https://slides.racinet.fr/2018/pyparis/
  

• Big forms with JSON schemas and transcrypt
  By: Philippe Entzmann, Aon France
  Slides: Philippe Entzmann-b8c559f7.pdf
  Video: here

• GraphQL in Python and Django
  By: Patrick Arminio, Verve
  Slides: Patrick Arminio-1cba4f64.pdf
  Video: here

• Inside Rapid.Space: Open Hardware and Free Software = Ultra Low Cost High Performance Cloud
  By: Jean-Paul Smets, Nexedi
  Slides: Jean-Paul Smets-d948a210.pdf
  Video: here

• Invitation to a New Kind of Database
  By: Sheer El Showk, Lore Ai
  Slides: Sheer El Showk-7f760599.pdf
  

• Serverless Python
  By: Michael Bright, @mjbright Consulting
  Slides: Michael Bright-319c4ecb.pdf
  Video: here

• The SIMPLE Framework, simplifying complex container clusters
  By: Mayank Sharma, CERN
  Slides: Mayank Sharma-d62634c7.pdf
  Video: here

• What is asyncio and when to use it, an example with WatchGhost
  By: Arthur Vuillard, hashbang.coop
  Slides / presentation material (online): https://static.hashbang.fr/pyparis18/#1
  Video: here

Devops

• Bonobo, Airflow and Grafana to visualize your business
  By: Romain Dorgueil, Makersquad
  Slides: Romain Dorgueil-44be21ce.pdf
  Video: here

• Python tooling for continuous deployment
  By: Arthur Lutz, Logilab
  Slides: Arthur Lutz-a4abc73a.pdf
  Video: here

• Scaling from 0 to 60k RPM
  By: Jean-Baptiste Aviat, Sqreen
  Slides: Jean-Baptiste Aviat-78d02f6a.pdf
  Video: here

Education

NOTE: Les présentations du track ‘Education’ ont lieu en français.

• Girls Can Code! summer camps: an experience of teaching computer science to young girls.
  By: Garance Gourdel, ENS Paris Saclay & Paul Guenezan, EPITA / Association Prologin
  Slides: Garance Gourdel+Paul Guenezan-5c5edc0d.pdf
  

• How we used Python to introduce teenagers to the fun of programming
  By: Anne-Marie Tousch, Criteo & Syrine Krichene, Criteo
  Slides: Anne-Marie Tousch+Syrine Krichene-178eaf43.pdf
  

• Python @ Sorbonne Université
  By: Frederic Peschanski, Sorbonne Université - LIP6
  Slides: Frederic Peschanski-4aba9775.pdf
  

• Python au Lycée: La réforme “Bac 2021” / L’informatique en quelques pointeurs
  By: Frederic Peschanski, Sorbonne Université - LIP6
  Slides: Frederic Peschanski-b3b418f7.pdf
  

• SageMath en 5 minutes
  By: Nicolas Thiery, Université Paris Sud
  Slides: Nicolas Thiery-3c76ea13.pdf
  Slides / presentation material (online): https://mybinder.org/v2/gh/nthiery/shared-sage-notebooks/master/?filepath=2018-11-14-PyParis-Education-SageMath.ipynb
  

Tutorials

• Dataviz with matplotlib and seaborn
  By: Francis Wolinski, Yotta Conseil
  Slides / presentation material (online): http://yotta-conseil.fr/python/Dataviz_with_matplotlib_and_seaborn_PyParis_2018.html
  

• GeoSpatial Data Analysis using Python
  By: Fereshteh Asgari, IRT SystemX
  Slides / presentation material (online): https://github.com/fereshteh-asg/PyParis2018_Geospatial_Data
  

• Machine learning using scikit-learn
  By: Guillaume Lemaitre, INRIA
  Slides / presentation material (online): https://github.com/glemaitre/pyparis-2018-sklearn
  

• Parallel Data Analysis with Dask
  By: Loïc Estève, Inria
  Slides / presentation material (online): https://github.com/mrocklin/pydata-nyc-2018-tutorial
  

• Python Micro-services with Kubernetes
  By: Michael Bright, @mjbright Consulting
  Slides / presentation material (online): https://github.com/ContainerOrchestration/Labs/blob/DevConf2018/Orchestration-Kubernetes/Kubernetes.md
  

• Understanding and diagnosing your machine-learning models
  By: Gael Varoquaux, Inria
  Slides / presentation material (online): http://gael-varoquaux.info/interpreting_ml_tuto/