word2vec Parameter Learning Explained

Understand

The word2vec model and application by Mikolov et al.

• have attracted a great amount of attention in recent two years.
• The vector representations of words learned by word2vec models have been shown to carry semantic meanings and are useful in various NLP tasks.
• As an increasing number of researchers would like to experiment with word2vec or similar techniques, I notice that there lacks a material that comprehensively explains the parameter learning process of word embedding models in details, thus preventing researchers that are non-experts in neural networks from understanding the working mechanism of such models.