Here we use word embedding instead of hot encoding, using a Word2Vec Learner node. The hidden layer size is set to 10, therefore …

This example shows how to transform a document into a vector using a word vector model and using these vectors for classification…

First, we read in a dataset containing sentences and assign each document a unique label. The unique label is used to create a do…

This example shows how to perform sentiment classification using word vectors. In this example, we use IMDb reviews which have ei…

First, we read in a dataset containing sentences and assign each document a unique label. The unique label is used to create a do…

This example shows how to perform sentiment classification using word vectors. In this example, we use IMDb reviews which have ei…