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SM

Scott Michael

Indiana University
IU Bloomington

9:00am PDT

Handling and analyzing spatial, spatiotemporal and movement data (Part 1) SIEPR 120

10:30am PDT

Handling and analyzing spatial, spatiotemporal and movement data (Part 2) SIEPR 120

1:00pm PDT

Using R with Jupyter notebooks for reproducible research (Part 1) SIEPR 120

2:30pm PDT

Using R with Jupyter notebooks for reproducible research (Part 2) SIEPR 120

10:30am PDT

Using Spark with Shiny and R Markdown SIEPR 130

10:48am PDT

RcppParallel: A Toolkit for Portable, High-Performance Algorithms SIEPR 130

11:06am PDT

Bayesian analysis of generalized linear mixed models with JAGS Barnes & McDowell & Cranston Taking R to new heights for scalability and performance SIEPR 130

11:24am PDT

Distributed Computing using parallel, Distributed R, and SparkR SIEPR 130

11:42am PDT

FlashR: Enable Parallel, Scalable Data Analysis in R SIEPR 130 How can I get everyone else in my organisation to love R as much as I do? Econ 140

1:00pm PDT

Continuous Integration and Teaching Statistical Computing with R SIEPR 130

1:18pm PDT

htmlwidgets: Power of JavaScript in R Lane & Lyons & Lodato

1:36pm PDT

What can R learn from Julia Lane & Lyons & Lodato

1:54pm PDT

Modeling Food Policy Decision Analysis with an Interactive Bayesian Network in Shiny SIEPR 120

2:12pm PDT

Teaching R to 200 people in a week SIEPR 130

4:45pm PDT

How to keep your R code simple while tackling big datasets Barnes & McDowell & Cranston

5:03pm PDT

Crowd sourced benchmarks Econ 140 New Paradigms In Shiny App Development: Designer + Data Scientist Pairing Lane & Lyons & Lodato

5:21pm PDT

Interactive Naive Bayes using Shiny: Text Retrieval, Classification, Quantification SIEPR 130

5:39pm PDT

Rho: High Performance R McCaw Hall RServer: Operationalizing R at Electronic Arts Barnes & McDowell & Cranston

10:48am PDT

Size of Datasets for Analytics and Implications for R Econ 140

11:06am PDT

Resource-Aware Scheduling Strategies for Parallel Machine Learning R Programs though RAMBO Econ 140

11:24am PDT

Grid Computing in R with Easy Scalability Econ 140 Heatmaps in R: Overview and best practices Barnes & McDowell & Cranston

11:42am PDT

Exploring the R / SQL boundary SIEPR 130

1:36pm PDT

Adding R, Jupyter and Spark to the toolset for understanding the complex computing systems at CERN's Large Hadron Collider McCaw Hall GNU make for reproducible data analysis using R and other statistical software Barnes & McDowell & Cranston

1:54pm PDT

Checkmate: Fast and Versatile Argument Checks SIEPR 130

2:12pm PDT

High performance climate downscaling in R SIEPR 120 Providing Digital Provenance: from Modeling through Production Barnes & McDowell & Cranston