kkanska / pydata-warsaw-conference-2018

PyData Warsaw Conference 2018

Links

• PyData Warsaw 2018 event website
• @PyDataWarsaw Twitter channel
• Graphic recordings by Ania Staśkiewicz
• Meetup website
• Photos
  • official: Google Photos album
  • post link to your gallery :)
• Video: TO BE POSTED
• Participant demographics analysis (draft version)

Slides and materials

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

Keynote

• Aleksandra Przegalińska - "Trust in the device dimensions of human chatbot relations"
• Lynn Cherny - Tl;dr: summarization
• Stefania Druga - "Cognimates: Read, Write and Tinker with AI"
• Gene Kogan - "The Neural Aesthetic"

Talks

Monday Nov. 19, 2018

• "PyTorch 1.0: now and in the future" - Adam Paszke
• "Deep Learning for 3D World: Point Clouds" - Marcin Mosiołek
• "Where visual meets textual. Luna - overview" - Sylwia Brodacka
• "Can you trust neural networks?" - Mateusz Opala
• "From Data to Deliverable" - Steph Samson
• "Overview of imbalanced data prediction methods" - Robert Kostrzewski
• "Recognizing products from raw text descriptions using “shallow” and “deep” machine learning" - Tymoteusz Wołodźko, Tomasz Płomiński
• "How I learnt computer vision by playing pool" - Łukasz Kopeć
• "Distributed deep learning and why you may not need it" - Jakub Sanojca, Mikuláš Zelinka
• "AI meets Art" - Agata Chęcińska
• "Hand in hand with weak supervision using snorkel" - Szymon Wojciechowski
• "3d visualisation in a Jupyter notebook" - Marcin Kostur, Artur Trzęsiok
• "Deep Learning Semantic Segmentation for Nucleus Detection" - Dawid Rymarczyk
• "Bit to Qubit: Data in the age of quantum computers" - Shahnawaz Ahmed
• "Transfer Learning for Neural Networks" - Dominik Lew
• "Spot the difference: train your image analytics model to recognize fine grained similarity" - Katarina Milosevic, Ioana Gherman,
• In Browser AI - neural networks for everyone - Kamila Stepniowska, Piotr Migdał
• "Using convolutional neural networks to analyze bacteriophages DNA" - Michał Jadczuk
• "Comixify: Turning videos into comics" - Adam Svystun, Maciej Pęśko,
• "High Performance Data Processing in Python" - Donald Whyte
• "What ad is this?" - Adam Witkowski
• Spammers vs. Data: My everyday fight - Juan De Dios Santos
• "Pragmatic application of Machine Learning in commercial products" - Łukasz Słabiński

Tuesday Nov. 20, 2018

• "Towards Data Pipeline Hyperparameter Optimization" - Alex Quemy
• "Similarity learning using deep neural networks" - Jacek Komorowski
• "Application of Recurrent Neural Networks to innovative drug design" - Rafał A. Bachorz
• "Computer vision challenges in drug discovery" - Dr Maciej Hermanowicz
• "Learning to rank @ allegro.pl" - Tomasz Bartczak, Ireneusz Gawlik
• "The smart shopping basket: A Case Study with deep learning, Intel Movidius and AWS" - Marcin Stachowiak, Michal Dura, Piotr Szajowski
• "It is never too much: training deep learning models with more than one modality" - Adam Słucki
• "Visualize, Explore and Explain Predictive ML Models" - Przemyslaw Biecek
• "The Dawn of Mind Reading in Python" - Krzysztof Kotowski
• "Uncertainty estimation and Bayesian Neural Networks" - Marcin Możejko
• "A deep revolution in speech processing and analysis" - Pawel Cyrta15:30
• "Predicting preterm birth with convolutional neural nets" - Tomasz Włodarczyk
• "Can you enhance that? Single Image Super Resolution" - Katarzyna Kańska
• "Burger Quest: finding the best hamburger in town!" - Roel Bertens
• "Hitting the gym: controlling traffic with Reinforcement Learning" - Steven Nooijen
• "Step by step face swap" - Sylwester Brzęczkowski
• "Optimizing Deep Neural Network Layer Topology with Delve" - Justin Shenk

Tutorials

• "Building Interactive Dashboards in Python - First steps with Dash" - Mikolaj Olszewski
• "Recognize drawings in the browser with Tensorflow.js" - Karol Majek, Monika Koprowska
• "Playing with CNN using Fashion-MNIST. Classification and what else can be done on it? - Rafał Wojdan
• "Peltarion: Build Deep Neural Networks without all the Overhead" - Justin Shenk
• "Structuring machine learning models by using pipelines" - Paweł Jankiewicz
• "Serverless Approach to Working with Data" - Jakub Nowacki
• "Introduction to Recommendation Systems" - Piotr Bigaj, Jakub Gasiewski, Przemek Kepczynski