Conference Schedule

Tutorials have separate tickets available on Eventbrite. Conference ticket does not include Tutorials.

Tutorials (Track 1 and Track 2) planned for Saturday, Dec 14, will be organized in Sages office, ul. Nowogrodzka 62c ("48" on intercom, 2nd floor)

Before coming to Tutorials please install required software listed on the Prerequisites page

General Sessions — Thursday Dec. 12, 2019

  Main Track Track 2 Track 3
9:00

Registration & Coffee
9:45

Opening Notes
10:00 The Ethics of Artificial Intelligence - What developers should know Vince Madai
10:45 Trusted AI – Building Reproducible, Unbiased and Robust AI Pipelines using the python OpenSource sta Romeo Kienzler
11:30

Coffee Break
12:00 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, Ioana Gherman
12:30

Technical Break
12:35 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
13:05

Technical Break
13:10 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
13:40

Lunch
15:00 TrashAsistant: A kivy App, which uses Deep Neural Networks, for helping trash segregation Olgun AYDIN, Krystian Zieliński Sound Modelling - parametric methods and deep learning representations to create and shape audio Pawel Cyrta Automation: Build A Training Pipeline Varun Kochar
15:30

Technical Break
15:35 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
16:05

Coffee Break
16:35 Learning to rank with the Transformer Tomasz Bartczak, Radoslaw Bialobrzeski In the service of the history. AI in archivistics. Adrian Boguszewski TDD shouldn't be TDDious Chris Sidebottom
17:05

Technical Break
17:10 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
17:40

Closing Notes
17:45
19:00

Afterparty - Location: Piwnica pod Harendą, Krakowskie Przedmieście Street 4/6. Remember to take your badge!
23:59

General Sessions — Friday Dec. 13, 2019

  Main Track Track 2 Track 3
9:20

Morning Coffee
9:50

Opening Notes
10:00 Transfer Learning - Entering a new era in NLP Malte Pietsch
10:45 Machine Learning can't do the thinking Inga Strumke
11:30

Coffee Break
12:00 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, Dominik Rusiecki
12:30

Technical Break
12:35 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
13:05

Lunch
14:25 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
14:55

Technical Break
15:00 Evaluation Metrics for Binary Classification: The Ultimate Guide Jakub Czakon Machine Learning on big data in security applications Yury Kasimov, Olga Petrova Machine Learning Spacecraft Designing for Cybersecurity Marina Volkova
15:30

Coffee break
16:00 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
16:30

Closing Notes
16:40

Tutorial Sessions (Nowogrodzka Street 62c) — Saturday Dec. 14, 2019

  Tutorial Track 1
9:30

Registration & Coffee
10:00 Straightforward introduction to Deep Learning Mikołaj Olszewski
12:00

Lunch
12:45 Straightforward introduction to Deep Learning Mikołaj Olszewski
14:45

Coffee Break
15:15 AWS Cloud data collecting with microcontrollers and MicroPython Michal Sulkiewicz
17:15

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