Python Natural Language Processing

Output of word2vec

This section is very important for your understanding because, after this point, whatever you understand will be just to achieve the output that you have set here. So, so far, we know that we want to develop the vector representation of a word that carries the meaning of the word, as well as to express the distribution similarity measure.

Now, I will jump towards defining our goal and output. We want to define a model that aims to predict a central word and words that appear in its context. So, we can say that we want to predict the probability of the context given the word. Here, we are setting up the simple prediction objective. You can understand this goal by referring to the following figure:

Figure 6.5: Help to understand ...