Python Deep Learning Projects

Defining our word2vec model

Now let's use gensim in our definition of the word2vec model. To begin, let's define a few hyperparameters for our model, such as the dimension, which means how many low-level features we want to learn. Each dimension will learn a unique concept of gender, objects, age, and so on.

Computational linguistics model tip #1: Increasing the number of dimensions leads to better generalization... but it also adds more computational complexity. The right number is an empirical question for you to determine as an applied AI deep learning engineer! Computational linguistics model tip #2: Pay attention to context_size. This is important because it sets the upper limit for the distance between the current and target word prediction ...