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proper structure of readme files - use bullet lists
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,6 @@ | ||
| - 14:00 - 14:15: Dividing space - spatially constrained regionalization method for large vector GIS data (Adam Dąbrowski) | ||
| - 14:15 - 14:30: [Multi-state churn analysis with a subscription product](https://github.com/g6t/mchurn) ([Marcin Kosiński](r-addict.com)) | ||
| - 14:30 - 14:45: Unnatural language processing ([Yizhar Izzy Toren](https://www.linkedin.com/in/ytoren)) | ||
| - 14:45 - 15:00: Tested on Humans (Mateusz Otmianowski) | ||
| - 15:00 - 15:15: [insuRvey: An R package for Instagram Based Surveys](https://github.com/olgnaydn/insurvey) ([Olgun Aydin](olgunaydin.com)) | ||
| - 15:15 - 15:30: [Highlight] The R language on the Microsoft AI Platform (Bart Czernicki) | ||
| - Dividing space - spatially constrained regionalization method for large vector GIS data (Adam Dąbrowski) | ||
| - [Multi-state churn analysis with a subscription product](https://github.com/g6t/mchurn) ([Marcin Kosiński](r-addict.com)) | ||
| - [Unnatural language processing](https://github.com/WhyR2018/presentations/blob/master/businessR/Unnatural%20Language%20Processing%20-%20WhyR%202018-07-04.pdf) ([Yizhar Izzy Toren](https://www.linkedin.com/in/ytoren)) | ||
| - Tested on Humans (Mateusz Otmianowski) | ||
| - [insuRvey: An R package for Instagram Based Surveys](https://github.com/olgnaydn/insurvey) ([Olgun Aydin](olgunaydin.com)) | ||
| - [Highlight] The R language on the Microsoft AI Platform (Bart Czernicki) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,6 @@ | ||
| 14:00 - 14:15: Marketing analytics the Shiny way (Adolfo Álvarez, Alina Tselinina) | ||
| 14:15 - 14:30: Using online updating algorithms to predict speedway results (Dawid Kałędkowski) | ||
| 14:30 - 14:45: [Highlight] auditor: an R package and methodology for validation of any statistical model (Alicja Gosiewska) | ||
| 14:45 - 15:00: [Artificial Intelligence in turn based strategy game](https://cdn.rawgit.com/lwawrowski/whyr2018_presentation/229fb363/presentation.html) (Łukasz Wawrowski) | ||
| 15:00 - 15:15: Get your Machine Learning workflow with under control with DVC (Mikołaj Bogucki) | ||
| 15:15 - 15:30: [Highlight] Correcting for SAMple BIAs with the sambia R package (Norbert Krautenbacher) | ||
| - Marketing analytics the Shiny way (Adolfo Álvarez, Alina Tselinina) | ||
| - Using online updating algorithms to predict speedway results (Dawid Kałędkowski) | ||
| - [Highlight] [auditor: an R package and methodology for validation of any statistical model](https://github.com/WhyR2018/presentations/blob/master/data-analysis/A_Gosiewska_auditor.pdf) (Alicja Gosiewska) | ||
| - [Artificial Intelligence in turn based strategy game](https://cdn.rawgit.com/lwawrowski/whyr2018_presentation/229fb363/presentation.html) (Łukasz Wawrowski) | ||
| - [Get your Machine Learning workflow with under control with DVC](https://github.com/WhyR2018/presentations/blob/master/data-analysis/MBogucki_Get_your_Machine_Learning_workflow_under_control_with_DVC.pdf) (Mikołaj Bogucki) | ||
| - [Highlight] Correcting for SAMple BIAs with the sambia R package (Norbert Krautenbacher) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,4 +1,4 @@ | ||
| 16:30 - 16:45: Tricks for faster R code (Tomasz Melcer) | ||
| 16:45 - 17:00: Using the GPU for speeding up custom models in R (Krzysztof Jędrzejewski) | ||
| 17:00 - 17:15: How to multiply your R computing power in 15 minutes for few bucks (Mikołaj Olszewski) | ||
| 17:15 - 17:30: Tell me which packages you use and I’ll tell you who you are (tidyverse vs data.table vs base R) (Anna Skrzydło, Bartosz Kowalski) | ||
| - Tricks for faster R code (Tomasz Melcer) | ||
| - [Using the GPU for speeding up custom models in R](https://github.com/WhyR2018/presentations/blob/master/high-performance-computing/WhyR%202018%20%E2%80%93%20Using%20the%20GPU%20for%20speeding%20up%20custom%20models%20in%20R.pdf) (Krzysztof Jędrzejewski) | ||
| - How to multiply your R computing power in 15 minutes for few bucks (Mikołaj Olszewski) | ||
| - Tell me which packages you use and I’ll tell you who you are (tidyverse vs data.table vs base R) (Anna Skrzydło, Bartosz Kowalski) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,3 +1,3 @@ | ||
| Data-driven indulgence (Piotr Zieliński) | ||
| R in pRoduction at KRuk (Aleksandra Gruchot) | ||
| Why R Is a Perfect Tool for the Debt Portfolio Valuation? (Grzegorz Chłapiński, Piotr Michalski) | ||
| - Data-driven indulgence (Piotr Zieliński) | ||
| - R in pRoduction at KRuk (Aleksandra Gruchot) | ||
| - Why R Is a Perfect Tool for the Debt Portfolio Valuation? (Grzegorz Chłapiński, Piotr Michalski) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| mlrFDA: functional data analysis with mlr (Florian Pfisterer) | ||
| Deep Learning in mlr (Janek Thomas) | ||
| rlR: Deep reinforcement learning with R (Xudong Sun) | ||
| Interpretable Machine Learning in R (Christoph Molnar) | ||
| Multilabel Classification with mlr (Quay Au) | ||
| - mlrFDA: functional data analysis with mlr (Florian Pfisterer) | ||
| - Deep Learning in mlr (Janek Thomas) | ||
| - rlR: Deep reinforcement learning with R (Xudong Sun) | ||
| - Interpretable Machine Learning in R (Christoph Molnar) | ||
| - Multilabel Classification with mlr (Quay Au) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,6 +1,6 @@ | ||
| 10:30 - 10:45: [Highlight] strideter: R package for identifying individual's steps from sub-second level accelerometry data of walking (Marta Karaś) | ||
| 10:45 - 11:00: [Highlight] R in LiFE ForBioSensing remote sensing project (Bartłomiej Kraszewski) | ||
| 11:00 - 11:15: Application of mlr and ggplot for machine-learning and visualisation on multiple depended variables (Jaroslaw Jasiewicz) | ||
| 11:15 - 11:30: Machine-learning and R for purposes of plastic surgery -- classification and attractiveness evaluation of facial emotions (Lubomír Štěpánek) | ||
| 11:30 - 11:45: PCRedux: machine learning helper tool for sigmoid curves (Stefan Rödiger) | ||
| 11:45 - 12:00: Method Comparisons with Applications in Biomarker Research and Development (Andre Beinrucker) | ||
| - [Highlight] [strideter: R package for identifying individual's steps from sub-second level accelerometry data of walking](https://github.com/WhyR2018/presentations/blob/master/r-in-natural-sciences/karas-accelerometry_data.pdf) (Marta Karaś) | ||
| - [Highlight] R in LiFE ForBioSensing remote sensing project (Bartłomiej Kraszewski) | ||
| - Application of mlr and ggplot for machine-learning and visualisation on multiple depended variables (Jaroslaw Jasiewicz) | ||
| - Machine-learning and R for purposes of plastic surgery -- classification and attractiveness evaluation of facial emotions (Lubomír Štěpánek) | ||
| - PCRedux: machine learning helper tool for sigmoid curves (Stefan Rödiger) | ||
| - Method Comparisons with Applications in Biomarker Research and Development (Andre Beinrucker) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,3 +1,3 @@ | ||
| 16:30 - 16:45: R as a tool for visualization of large demographic datasets (Anna Dmowska) | ||
| 16:45 - 17:00: Making Shiny shine brighter with 6 useful packages (Krystian Igras) | ||
| 17:00 - 17:15: Webscraping with RSelenium (Pieter Krsteff-Jantcheff) | ||
| - 16:30 - 16:45: R as a tool for visualization of large demographic datasets (Anna Dmowska) | ||
| - 16:45 - 17:00: Making Shiny shine brighter with 6 useful packages (Krystian Igras) | ||
| - 17:00 - 17:15: Webscraping with RSelenium (Pieter Krsteff-Jantcheff) |