Spark ML: Building the model

- [Instructor] Continuing from the previous movie,…in part two of MLLib with Spark…we're going to put all the features in to a single vector,…create an array to list the names…of all the nonfeature columns…zip, zipcode, count, call it nonfeature columns.…Create a list of names called feature columns,…which excludes the columns in nonfeature columns…and print the feature columns.…So let's go ahead and do that.…So there's our list, and now we're going to call…from the pyspark.ml library, the vector assembler.…We're going to add a features vector to the prepped dataset.…

We're going to call the new dataset final prep.…And then we're going to display only the zip code…and features from final prep.…Now, we're going to display the feature columns…graphed out against each other as a scatter plot.…So we are excluding some of the features…that we're not interested in.…We're going to visualize this as a scatter plot.…Let's look at our plot options.…That looks good, so now here's a usability tip.…This is really hard to see. Let's drag this way out.…