Why R? 2019 Presentations This repository consist of presentations prepared by the authors. 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, Patryk Wielopolski 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 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?