Deep Learning with R Cookbook

How it works...

In step 1, we loaded the iris data from the datasets library in R. It is always advised to be aware of the data and its characteristics before we start building models. Hence, we studied the structure and type of the variables in the data. We saw that apart from Species (our response (target) variable), all the other variables were numeric. Then, we checked the dimensions of our dataset.

The summary() function shows us the distribution of variables and the central tendency metric for each of these variables in the data. The head() function, by default, displays only the first five rows of the dataset.

You can use head() to display any number of records. To do this, you need to pass the number of records as an argument in the ...