Generate some dummy data for feed forward neural network

ffnetwork_dummydata.py

#creating my own color map for better visualization
my_cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", ["red","yellow","green"])

#Generating 1000 observations with 4 labels - multi class
data, labels = make_blobs(n_samples=1000, centers=4, n_features=2, random_state=0)
print(data.shape, labels.shape)

#visualize the data
plt.scatter(data[:,0], data[:,1], c=labels, cmap=my_cmap)
plt.show()

#converting the multi-class to binary 
labels_orig = labels
labels = np.mod(labels_orig, 2)
plt.scatter(data[:,0], data[:,1], c=labels, cmap=my_cmap)
plt.show()

#split the binary data
X_train, X_val, Y_train, Y_val = train_test_split(data, labels, stratify=labels, random_state=0)
print(X_train.shape, X_val.shape)