R-Machine-Learning-Legacy
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dlab-berkeley
D-Lab's 6 hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.
To show if balances are different for default status: plot(default$balance ~ default$default)
Solutions for 04_regularization should include: # Import data penguins % filter(!is.na(bill_length_mm)) # Set seed set.seed(23) # Perform split penguin_split % initial_split(prop = 0.80) penguins_train
It would be helpful to add a short summary of the packages and functions introduced with their respective uses at the end of the third module (pre-processing)!
'docs' folder doesn't exist in the R-Machine-Learning-main project, so there's an error that pops up when you open it. doesn't impact running code
I delivered the workshop with these current materials, and things went pretty smoothly, but it's too much material for two 3 hour workshops. I'd recommend splitting this workshop into either...
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D-Lab's 6 hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.