What are all the 300-dimensional vectors used for google word2vec model?

Hi
Im new to nlp and just testing waters now with models, frameworks, techniques and related math.

Im looking at this model:
https://code.google.com/archive/p/word2vec/

Can someone explain what are all the "300 embeddings" in
https://code.google.com/archive/p/word2vec/,
model .bin can be found here: https://drive.google.com/file/d/0B7XkCwpI5KDYNlNUTTlSS21pQmM/edit?usp=sharing ?

Here's the example for the word expected:

```
expected 0.06347656 0.265625 0.06982422 -0.008728027 -0.17578125 0.012573242 0.18457031 -0.037841797 0.20898438 0.087890625 -0.064941406 0.125 0.06689
453 -0.18359375 -0.07080078 0.033935547 0.052978516 -0.14257812 0.12597656 0.08544922 -0.33398438 0.018310547 0.043701172 -0.15917969 -0.06542969 -0.1
2060547 -0.013122559 …

google languagetechnology word2vec