Ben's personal repo
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bbest Goto Github PK
Name: Ben Best
Type: User
Location: Santa Barbara, CA
Blog: http://benbestphd.com
Ben Best's Projects
r4ioos
demo of R for automation & reporting
rcharts
Interactive JS Charts from R
registry
Getting data services registered in the IOOS Service Registry
research-highlights
Multimedia invitation to seminar, research and lab for Cal State Channel Islands
rgee
Google Earth Engine for R
rmarkdown-example
R Markdown example showing figures & tables with captions, equations, inline R values and references with a Zotero library
rmarkdown-website-examples
Examples of R Markdown Websites
robis
R client for the OBIS API
routing
Routing ships to avoid whale strike
rss_article_recommender
Recommends journal articles from rss feeds based on articles you have stored in your citation manager.
sbdev
help with Bren GP sbdevelopment
sf
Simple Features for R
shiny-ck
Shiny app for Channel Keeper
shiny-intro
introduction to Shiny interactive application framework using R
shiny-multi
multiselect w/ shiny
shiny_sandbox
Exploring Shiny from RStudio
shinyjstutorials
tutorials materials on R/Shiny bindings to popular javascript libraries
shipwrecks
Shipwrecks database and analyses
siting
Siting offshore wind energy development in the US Atlantic to minimize impacts on birds in space and cetaceans in time
siting-sdm-uncertainty
incorporating uncertainty in species distribution models as loss function for spatial decision making
siting-sim
utility simulation
spatial_analysis2_r
Focusing on shapefiles and polygons,
ssp
Repository of the Project Simulated Sampling Procedure for Community Ecology
starter-academic
🎓 创建一个学术网站. Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify.
students
student directory, for practicing doing pull requests
sunburstr
R htmlwidget for sequence sunburst
talks
Presentations, usually using Rmarkdown
tbep-os-responses
demo
tbep-os-responses_0
Tampa Bay Estuary Program - Open Science - Responses
tensorflow
Computation using data flow graphs for scalable machine learning
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