diff --git a/README.md b/README.md
index e98e063..3ff2e65 100644
--- a/README.md
+++ b/README.md
@@ -20,18 +20,19 @@ The demo below shows how SVMs work:
 
 ```julia
 # To show how SVMs work, we'll use Fisher's iris data set
-using SVM
+# Temporally, following order is required
 using RDatasets
+using SVM
 
 # We'll learn to separate setosa from other species
-iris = data("datasets", "iris")
+iris = dataset("datasets", "iris")
 
 # SVM format expects observations in columns and features in rows
 X = array(iris[:, 1:4])'
 p, n = size(X)
 
 # SVM format expects positive and negative examples to +1/-1
-Y = [species == "setosa" ? 1.0 : -1.0 for species in iris[:, "Species"]]
+Y = [species == :setosa ? 1.0 : -1.0 for species in iris[:, "Species"]]
 
 # Select a subset of the data for training, test on the rest.
 train = randbool(n)
@@ -40,7 +41,7 @@ train = randbool(n)
 model = svm(X[:,train], Y[train])
 
 # And now evaluate that model on the testset
-accuracy = nnz(predict(model, X[:,~train]) .== Y[~train])/nnz(~train)
+accuracy = countnz(predict(model, X[:,~train]) .== Y[~train])/countnz(~train)
 ```
 
 You may specify non-default values for the various parameters: