Update readme.md

readme.md

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 #Parametric t-SNE
 
-Laurens Van Der Maaten's [parametric implementation](https://lvdmaaten.github.io/publications/papers/AISTATS_2009.pdf) of t-SNE. The original implementation is for Matlab, here we are running in Octave with oct2py.
+Laurens Van Der Maaten's [parametric implementation](https://lvdmaaten.github.io/publications/papers/AISTATS_2009.pdf) of t-SNE.
 
-I'm currently working on porting the technique to a more recent toolkit.
+Laurens' original implementation is for Matlab, here we are running in Octave with oct2py in the notebook `Parametric t-SNE (Original)`. This code can take hours to complete.
+
+In the `Parametric t-SNE (Keras)` notebook there is an implementation of the same technique by reimplementing all functions in Python with numpy and [Keras](https://keras.io/). The code runs significantly faster (on my machine, 20 minutes). There are also some work-in-progress experiments, like using the pairwise probabilty embedding to pre-train the weights of an autoencoder, which appears to converge to a lower reconstruction error than a vanilla autoencoder.
 
 ## Setup
 
@@ -12,4 +14,4 @@ On OS X:
 $ brew install octave
 $ pip install -r requirements.txt
 $ jupyter notebook
-```
+```