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Tuesday
, July 4
2.01
9:30am •
Introduction to Bayesian inference with JAGS
11:30am •
Introduction to Bayesian inference with JAGS
2:00pm •
Modelling the environment in R: from small-scale to global applications
4:00pm •
Modelling the environment in R: from small-scale to global applications
2.02
9:30am •
Data Carpentry: Open and Reproducible Research with R
11:30am •
Data Carpentry: Open and Reproducible Research with R
2:00pm •
R package development with R-hub
4:00pm •
R package development with R-hub
3.01
9:30am •
Introduction to parallel computing with R
11:30am •
Introduction to parallel computing with R
2:00pm •
data.table for beginners
4:00pm •
data.table for beginners
3.02
9:30am •
Solving iteration problems with purrr
11:30am •
Solving iteration problems with purrr
2:00pm •
Introduction to Natural Language Processing with R
4:00pm •
Introduction to Natural Language Processing with R
4.01
9:30am •
Sports Analytics with R
11:30am •
Sports Analytics with R
2:00pm •
Introduction to optimal changepoint detection algorithms
4:00pm •
Introduction to optimal changepoint detection algorithms
4.02
9:30am •
Dose-response analysis using R
11:30am •
Dose-response analysis using R
2:00pm •
OpenML: Connecting R to the Machine Learning Platform OpenML
4:00pm •
OpenML: Connecting R to the Machine Learning Platform OpenML
4.03
9:30am •
Geospatial visualization using R
11:30am •
Geospatial visualization using R
2:00pm •
Spatial data in R: new directions
4:00pm •
Spatial data in R: new directions
CATERING POINTS
11:00am •
COFFEE BREAK
1:00pm •
LUNCH
3:30pm •
COFFEE BREAK
5:30pm •
WELCOME RECEPTION
PLENARY
9:30am •
Rcpp: From Simple Examples to Machine Learning
11:30am •
Rcpp: From Simple Examples to Machine Learning
2:00pm •
Efficient R Programming
4:00pm •
Efficient R Programming
Wild Gallery
8:00am •
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