title: Visualise word2vec generated from gensim using t-sne
body: <p>I have trained a doc2vec and corresponding word2vec on my own corpus using gensim. I want to visualise the word2vec using t-sne with the words. As in, each dot in the figure has the "word" also with it.</p>
  
  <p>I looked at a similar question here : <a href="https://stackoverflow.com/questions/40581010/how-to-run-tsne-on-word2vec-created-from-gensim">t-sne on word2vec</a></p>
  
  <p>Following it, I have this code : </p>
  
  <p>import gensim
  import gensim.models as g</p>
  
  <pre><code>from sklearn.manifold import TSNE
  import re
  import matplotlib.pyplot as plt
  
  modelPath="/Users/tarun/Desktop/PE/doc2vec/model3_100_newCorpus60_1min_6window_100trainEpoch.bin"
  model = g.Doc2Vec.load(modelPath)
  
  X = model[model.wv.vocab]
  print len(X)
  print X[0]
  tsne = TSNE(n_components=2)
  X_tsne = tsne.fit_transform(X[:1000,:])
  
  plt.scatter(X_tsne[:, 0], X_tsne[:, 1])
  plt.show()
  </code></pre>
  
  <p>This gives a figure with dots but no words. That is I don't know which dot is representative of which word. How can I display the word with the dot?</p>