Cost sensitive classification with individual cost
There are two types of classification costs: per class, and per instance.

In keras, for instance cost, we assign a cost to each training sample by feeding sample_weight to .fit. For example, if we have four training samples in rows 1, 2, 3, and 4, with misclassification costs 2.5, 1.5, 1.0, and 1.0, we feed sample_weight=[2.5, 1.5, 1.0, 1.0]. 

For class cost, if there are three classes 0, 1, and 2, with misclassification costs 1.0, 3.0, 1.0, we feed class_weight=[1.0, 3.0, 1.0].

Here is a step-by-step classification example in Keras.

You should feed your weights in this line:

model.fit(train_images, train_labels, epochs=5)