Keras- Embedding layer

Question

What does input_dim, output_dim and input_length mean in:

Embedding(input_dim, output_dim, input_length)

Answer 1

By taking a look at the keras documentation for the layer you see this:

Embedding(1000, 64, input_length=10)
#the model will take as input an integer matrix of size (batch, input_length).
#the largest integer (i.e. word index) in the input should be no larger than 999 (vocabulary size).
#now model.output_shape == (None, 10, 64), where None is the batch dimension.

By using the values you gave in your post you can try to grasp the idea of this method and can come up with this settings:

• input_dim=38
• input_length=75

while output_dim is a model parameter, which you still have to determine (and maybe have to try different values to find the optimal one).

Edit: You can find additional information about embedding layers here.