Visualizing word embeddings with TensorBoard
When we wanted to visualize word embedding in Chapter 3, Word2vec – Learning Word Embeddings, we manually implemented the visualization with the t-SNE algorithm. However, you also could use TensorBoard for visualizing word embeddings. TensorBoard is a visualization tool provided with TensorFlow. You can use TensorBoard to visualize the TensorFlow variables in your program. This allows you to see how various variables behave over time (for example, model loss/accuracy), so you can identify potential issues in your model.
TensorBoard enables you to visualize scalar values and vectors as histograms. Apart from this, TensorBoard also allows you to visualize word embeddings. Therefore, it takes all the required code implementation away from you, if you need to analyze what the embeddings look like. Next we will see how we can use TensorBoard to visualize word embeddings. The code for this exercise is provided in tensorboard_word_embeddings.ipynb...
