title: what actually word embedding dimensions values represent?
body: <p>I have a doubt in word2vec and word embedding , I have downloaded GloVe pre-trained word embedding (shape 40,000 x 50)  and using this function to extract information from that:</p>
  
  <pre><code>import numpy as np
  def loadGloveModel(gloveFile):
      print ("Loading Glove Model")
      f = open(gloveFile,'r')
      model = {}
      for line in f:
          splitLine = line.split()
          word = splitLine[0]
          embedding = np.array([float(val) for val in splitLine[1:]])
          model[word] = embedding
      print ("Done.",len(model)," words loaded!")
      return model
  </code></pre>
  
  <p>Now if I call this function for word 'python'  something like :</p>
  
  <pre><code>print(loadGloveModel('glove.6B.100d.txt')['python'])
  </code></pre>
  
  <p>it gives me 1x50 shape vector like this:</p>
  
  <pre><code>[ 0.24934    0.68318   -0.044711  -1.3842    -0.0073079  0.651
   -0.33958   -0.19785   -0.33925    0.26691   -0.033062   0.15915
    0.89547    0.53999   -0.55817    0.46245    0.36722    0.1889
    0.83189    0.81421   -0.11835   -0.53463    0.24158   -0.038864
    1.1907     0.79353   -0.12308    0.6642    -0.77619   -0.45713
   -1.054     -0.20557   -0.13296    0.12239    0.88458    1.024
    0.32288    0.82105   -0.069367   0.024211  -0.51418    0.8727
    0.25759    0.91526   -0.64221    0.041159  -0.60208    0.54631
    0.66076    0.19796   -1.1393     0.79514    0.45966   -0.18463
   -0.64131   -0.24929   -0.40194   -0.50786    0.80579    0.53365
    0.52732    0.39247   -0.29884    0.009585   0.99953   -0.061279
    0.71936    0.32901   -0.052772   0.67135   -0.80251   -0.25789
    0.49615    0.48081   -0.68403   -0.012239   0.048201   0.29461
    0.20614    0.33556   -0.64167   -0.64708    0.13377   -0.12574
   -0.46382    1.3878     0.95636   -0.067869  -0.0017411  0.52965
    0.45668    0.61041   -0.11514    0.42627    0.17342   -0.7995
   -0.24502   -0.60886   -0.38469   -0.4797   ]
  </code></pre>
  
  <p>I need help in understanding the output matrix. What does these value represent and there significance in generating new word</p>