Fix Python – NaN loss when training regression network

I have a data matrix in “one-hot encoding” (all ones and zeros) with 260,000 rows and 35 columns. I am using Keras to train a simple neural network to predict a continuous variable. The code to make the network is the following:
model = Sequential()
model.add(Dense(1024, input_shape=(n_train,)))

Fix Python – Deep-Learning Nan loss reasons

Perhaps too general a question, but can anyone explain what would cause a Convolutional Neural Network to diverge?
I am using Tensorflow’s iris_training model with some of my own data and keep getting

ERROR:tensorflow:Model diverged with loss = NaN.