PyData-Warsaw-Conference-2019

Links

Slides and materials

Feel invited to Pull Request with link to slides or the project website.

Keynote

  • The Ethics of Artificial Intelligence - What developers should know - Vince Madai
  • Trusted AI – Building Reproducible, Unbiased and Robust AI Pipelines using the python OpenSource sta - Romeo Kienzler
  • Transfer Learning - Entering a new era in NLP - Malte Pietsch
  • Machine Learning can't do the thinking - Inga Strumke

Talks

Thursday Dec. 12, 2019

  • Disease Modeling with Scipy and PyMC - Dean Langsam
  • Transfer learning for image recognition in healthcare industry - Michał Kierzynka
  • Geospatial analysis made easy with PostGIS and Geoalchemy - Nicolas Pierre
  • The NLU Orchestra - Amit Beka
  • keras-fsl: Fast model builder for production ready few shot learning algorithms - Dr. Clément Walter
  • How to structure PySpark application - Przemek Chrabka
  • Reproducible Machine Learning - Mateusz Opala
  • How to numerically represent semi-structured log data for anomaly detection? - Marcin Kowiel
  • Modern Machine Learning flow with Quilt and Polyaxon - Robert Kostrzewski
  • TrashAsistant: A kivy App, which uses Deep Neural Networks, for helping trash segregation - Olgun AYDIN
  • Sound Modelling - parametric methods and deep learning representations to create and shape audio - Pawel Cyrta
  • Automation: Build A Training Pipeline - Varun Kochar
  • Posterior Collapse in Deep Generative models - Michał Jamroż
  • Generative Text Modelling: Scratching the surface - Tomasz Dziopa
  • ML model from an idea to production with the help of Python - Martyna Urbanek-Trzeciak
  • Learning to rank with the Transformer - Tomasz Bartczak
  • In the service of the history. AI in archivistics. - Adrian Boguszewski
  • TDD shouldn't be TDDious - Chris Sidebottom
  • Analysing Russian Troll Tweets data with Python - Mia Polovina
  • What's coming in Apache Airflow 2.0 - Jarek Potiuk
  • Unsupervised learning for news summarisation - Jakub Kubajek

Friday Dec. 13, 2019

  • Anyone can Build Great Deep Learning Applications - Deep Numpy - Cyrus Vahid
  • Command line language – where NLP and cyber security meets - Zuzanna Kunik
  • How we personalized onet.pl with multi-armed bandits - Artur Bujak
  • How to manage data-related projects and not fail (too often)? - Jakub Nowacki
  • How to effectively extract image features – let’s play with OpenCV API! - Filip Geppert
  • How to efficiently model learner’s knowledge with recurrent neural networks - Mateusz Otmianowski
  • Visual Search @ allegro.pl - Marcin Tuszyński
  • Predicting flight compensation - a case study - Adam Witkowski
  • Sentiment analysis of tweets in Polish language using deep learning - Joanna Piwko
  • Evaluation Metrics for Binary Classification: The Ultimate Guide - Jakub Czakon
  • Machine Learning on big data in security applications - Yury Kasimov
  • Machine Learning Spacecraft Designing for Cybersecurity - Marina Volkova
  • Football video analysis using Deep Learning - Jacek Komorowski
  • Adding Narrative to BI Dashboards with Natural Language Generation - Žygimantas Medelis
  • Detection of solar panels based on aerial images of the city of Poznań using deep neural networks - Michel Voss

Tutorials

  • Straightforward introduction to Deep Learning - Mikołaj Olszewski
  • AWS Cloud data collecting with microcontrollers and MicroPython - Michal Sulkiewicz