Hands-On Deep Learning Algorithms with Python

Building the model

Now let's build our model. Let's define some of the important hyperparameters that our model needs:

• The size parameter represents the size of the vector, that is, dimensions of our vector, to represent a word. The size can be chosen according to our data size. If our data is very small, then we can set the size to a small value, but if we have a significantly large dataset, then we can set the size to 300. In our case, we set the size to 100.
• The window_size parameter represents the distance that should be considered between the target word and its neighboring word. Words exceeding the window size from the target word will not be considered for learning. Typically, a small window size is preferred.
• The min_count parameter ...