James Pooley's repositories
shiny-resources
An annotated bibliography of resources for building Shiny apps
brain-age-prediction
Notes on developmental trajectories, predicting brain maturation, effects of head motion on sMRI, and qMRI and brain development
adv-r
Advanced R: a book
archived-jamespooley.github.io
https://jamespooley.github.io
cmus
Small, fast and powerful console music player for Unix-like operating systems.
dammmdatagen
Marketing Mix Modeling Data Generator
design
Tidyverse design principles
discogs_analysis
Sundry analyses of Discogs data
dotfiles
All (or a least a decent number of) my configs
dotvim
My Vim environment
engineering-shiny-book
Engineering Production-Grade Shiny Apps — To be published in the R Series in 2020.
fight-churn
Code from the book Fighting Churn With Data
linux-dev-env
Scripts to get my 🐧 environment up and running
mastering-shiny
Mastering Shiny: a book
motion-correction
Code for exploring the effect of motion of sMRI-derived measures
Nvim-R
Vim plugin to work with R
nyc_311_complaints
☎️ Source, clean, and wrangle NYC 311 complaints data
plotly_book
plotly for R book
qmri-notes
Notes on quantiative MRI techniques
quality-ratings
Models for sMRI image quality ratings
quotations
Quotations I like the sound of, posting != endorsement in all cases, etc. etc.
resources
List of statistics and programming resources I find useful
Robyn
Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) code from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for granular datasets with many independent variables and therefore especially suitable for digital and direct response advertisers with rich dataset.