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DESCRIPTION
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DESCRIPTION
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Package: learndrake
Title: Short Course on the Drake R Package
Description: Ambitious workflows in R can be difficult to manage.
A single round of computation can take several hours to complete,
and routine updates to the code and data tend to invalidate
hard-earned results. You can enhance the maintainability, hygiene,
speed, scale, and reproducibility of such projects with
the drake R package. drake resolves the dependency structure
of your analysis pipeline, skips tasks that are already up to date,
executes the rest with optional distributed computing,
and organizes the output so you rarely have to think about data files.
The slides, notebooks, and Shiny apps in this package
teach how to create and maintain machine
learning projects with drake-powered automation.
Version: 0.0.2.9000
License: GPL-3
URL: https://github.com/wlandau/learndrake
BugReports: https://github.com/wlandau/learndrake/issues
Authors@R: c(
person(
family = "Landau",
given = c("William", "Michael"),
email = "[email protected]",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-1878-3253")
),
person(
family = "Eli Lilly and Company",
role = "cph"
))
SystemRequirements:
Python (>= 2.7.0),
TensorFlow (https://www.tensorflow.org/),
Keras >= 2.0 (https://keras.io)
Depends:
R (>= 3.5.0)
Imports:
drake (>= 7.6.1),
drakeplanner,
future,
future.callr,
fs (>= 1.3.0),
keras,
learnr,
lubridate,
recipes,
rmarkdown,
rsample,
shiny,
styler,
tensorflow,
tidyverse,
visNetwork,
yardstick
Suggests:
prettycode,
rsconnect,
shinytest,
tidyselect (>= 0.2.4),
testthat (>= 2.1.0),
withr
Remotes:
ropensci/drake,
wlandau/drakeplanner
Encoding: UTF-8
Language: en-US
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.0.2