| Session |
Author |
Title |
| Keynotes |
Jakub Nowosad |
The landscape of spatial data analysis in R |
| Keynotes |
Marvin N. Wright |
Random forests: The first-choice method for every data analysis? |
| Keynotes |
Paula Brito |
Modelling and Analysing Interval Data in R |
| Keynotes |
Sigrid Keydana |
tfprobably correct - adding uncertainty to deep learning with TensorFlow Probability |
| Keynotes |
Steph Locke |
Is data science experimenting on people? |
| Keynotes |
Wit Jakuczun |
Always Be Deploying. How to make R great for machine learning in (not only) Enterprise |
| API |
Piotrek Ciurus |
Automating Google Slides creation |
| API |
Florent Bourgeois |
Bringing interactivity into engineering courses with BERT-based Excel-R applications |
| API |
Leszek Sieminski |
Google PageSpeed with R |
| BIO |
Jaroslaw Chilimoniuk |
AmyloGram: the R package and a Shiny server for amyloid prediction |
| BIO |
Olga Kaminska |
Machine Learning usage for prediction of state change in bipolar disorder |
| BIO |
Leon Eyrich Jessen |
Tidysq for Working with Biological Sequence Data in ML Driven Epitope Prediction in Cancer Immunotherapy |
| BIO |
Jagoda Glowacka |
Multicenter study, 33 TB of data and the goal: predicting epilepsy |
| BIO |
Weronika Puchala |
R for experimentalists: HDX-MS example |
| BIO |
Piotr Nowosielski |
R in Ministry of Health |
| Business |
Artur Suchwałko |
How R helps us with delivering Machine Learning projects |
| Business |
Richard Louden |
Integrating R and Python for reproducible business analytics |
| Business |
Francois Jacquet |
R for Entrepreneurs : supply chain automation case |
| EDA |
Lidia Kolakowska |
How to deal with nested lists in R? Using the purrr, furrr and future packages in practice |
| EDA |
Tomasz Żółtak |
MasteR of Tables |
| EDA |
Mateusz Staniak |
R Tools for Automated Exploratory Data Analysis |
| GEO |
Krystian Andruszek |
Features of districts of Warsaw visible from space |
| GEO |
Çizmeli Servet Ahmet |
Geospatial data analysis and visualization in R |
| GEO |
Maria Mikos |
Spatial econometrics with self-made weighting matrixes - uncovering similarity of sample with machine learning results and categorical variables |
| Lightnings |
Anne Bras |
Crazy Sequential Representations - The 10958 Problem |
| Lightnings |
Hubert Baniecki |
D3 + DALEX = Interactive Studio with Explanations for ML Predictive Models in R |
| Lightnings |
Dawid Kaledkowski |
Don't walk, run! runner package for rolling window functions |
| Lightnings |
Ioan Gabriel Bucur |
RUcausal: An R package for Representing Uncertainty in causal discovery |
| Lightnings |
Mateusz Kobylka |
RME: interpretable explainations for sequence models |
| Lightnings |
Kamil Sijko |
Selling solutions based on R (which is GPL licensed). Is this possible? |
| Lightnings |
Patrik Drhlik |
Using R6 classes to communicate with a REST API |
| Lightnings |
Dominik Rafacz |
AmyloGram 2.0: MBO in the prediction of amyloid proteins |
| Lightnings |
Krzysztof Kania |
bdl: interface and tools to Local Data Bank API |
| Lightnings |
Katarzyna Sidorczuk |
PepBay: Implementation of Bayesian inference in the analysis of peptide arrays |
| Lightnings |
Agnieszka Otreba-Szklarczyk |
R in marketing surveys - how to speed up the analysis of open ended questions |
| Lightnings |
Łukasz Wawrowski |
Testing artificial intelligence algorithms in games with Shiny |
| Lightnings |
Anna Kozak |
vivo: Is it Victoria In Variable impOrtance detection? |
| Lightnings |
Rafal Wozniak |
What we don't have but need. Some missing R functions in teaching econometrics |
| Modelling |
Bartosz Kolasa |
Custom loss functions for binary classifications problem with highly imbalanced dataset using Extremely Gradient Boosted Trees |
| Modelling |
Michał Podsiadło |
Investment Portfolio Optimization |
| Modelling |
Barbara Jancewicz |
Multidimensional Scaling with the smacof package |
| Modelling |
Ken Benoit, Damian Rodziewicz |
NLP models for the masses with the Quanteda package and a Shiny interface |
| Modelling |
Adam Bień |
Detecting topics in civil service job offers using Latent Dirichlet Allocation model |
| Modelling |
Hamdan Azhar |
How I became an emoji data scientist (using R!) |
| Modelling |
Matteo Fasiolo |
Generalized additive models for short-term electricity demand forecasting |
| Modelling |
Tamas Burghard |
Using categorical embeddings (deep learning) in boosting models |
| Philosophy |
Dorota Celinska-Kopczynska |
Collective intelligence in GitHub teams |
| Philosophy |
Colin Gillespie |
Hacking R as a script kiddie |
| Philosophy |
Colin Fay |
R & MicroService |
| Philosophy |
Olga Mierzwa-Sulima |
Traits of a world-class data scientist |
| Scoring |
Michal Rudko |
Experiment management using mlflow and R |
| Scoring |
Jacek Wolak |
Forecasting rental prices of flats in Krakow |
| Scoring |
Karol Klimas |
Predict, vote and elect with R |
| Shiny |
Pawel Sakowski |
A Shiny Real-time Application for Backtesting Investment Strategies on Regulated and Crypto Markets |
| Shiny |
Jakub Małecki, Jakub Stepniak |
Challenges of Shiny application development at scale |
| Shiny |
Theo Roe |
Improving the communication of environmental data using Shiny |
| Shiny |
Tomasz Koc, Piotr Wójcik |
Shiny application for algorithmic trading |
| Vision |
Olgun Aydin |
A Case Study for Image Classification using Transfer Learning |
| Vision |
Michel Voss |
Detection of solar panels based on aerial images using deep learning |
| Vision |
Lubomir Stepanek |
Facial landmarking made (possible and) easy with R! |
| Vision |
Pablo Maldonado |
DeepSport: A Shiny app for sports video analysis |
| Vision |
Michal Maj |
Semantic segmentation using U-Net with R |
| XAI |
Szymon Maksymiuk |
Compare predictive models created in different languages with DALEX and friends |
| XAI |
Blazej Kochanski |
Benefits of better credit scoring |
| XAI |
Aleksandra Grudziaz |
survxai: how to explain predictions for survival models? |
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