# How are the embedding and context matrices created and updated in word embedding?

I am struggling to understand how word embedding works, especially how the embedding matrix $$W$$ and context matrix $$W'$$ are created/updated. I understand that in the Input we may have a one-hot encoding of a given word, and that in the output we may have the word the most likely to be nearby this word $$x_i$$

Would you have any very simple mathematical example?