hyperparameter tuning of learning rate, lambda
add some text about adam optimizer and more conservative vs aggressive
inputs sensitivity analysis for starting parameter guesses
library(ggplot2)
# volcano is a matrix; convert to data frame
volcano_df <- as.data.frame(as.table(volcano))
names(volcano_df) <- c("x", "y", "z")
ggplot(volcano_df, aes(x, y, z = z)) +
geom_contour_filled(bins = 15) +
labs(fill = "Elevation") +
theme_minimal()
# need to convert loss from final fis and M at various different levels
# and capture that landscape
# from your expand.grid start params