Course materials for Applied Machine Learning course in 2019 in London

• November 18, 2019—November 19, 2019 9:00 AM-5:00 PM

• Hilton London Paddington (146 Praed Street, London, LND W2 1EE, map)

These will be posted a day before the workshop. The slides are in HTML, so browser that uses javascript is required.

We will have RStudio server pro instances will all of the packages installed as well as the above GitHub repository available.

If you would like to run R locally, the installation instructions are:

install.packages(
  c(
    'AmesHousing',
    'C50',
    'devtools',
    'discrim',
    'earth',
    'ggthemes',
    'glmnet',   # See important note below
    'klaR',
    'lubridate',
    'party',
    'pROC',
    'rpart',
    'stringr',
    'textfeatures',
    'tidymodels'
  ),
  repos = "http://cran.rstudio.com"
)
devtools::install_github("tidymodels/recipes")
devtools::install_github("tidymodels/dials")
devtools::install_github("tidymodels/textrecipes")
devtools::install_github("r-lib/cli")
devtools::install_github("koalaverse/vip")
devtools::install_github("tidymodels/tune")

** Important note! ** A new version of glmnet was released on 2019-11-09. Although it states that it depends on R (≥ 3.5.0), it may not install on R versions < 3.6.0.

We will be on-site at least 30min before the workshop commences in case you need any help getting packages installed. Prior to this, you can email [email protected] with questions.

If you want to read up a bit about predictive modeling before the workshop, check out chapter 1 and chapter 3 of Feature Engineering and Selection.