Update README.md

2016-11_Seminar/README.md

@@ -83,5 +83,15 @@ This is an implementation for relation extraction. We use the [SemEval 2010 - Ta
 
 **Code:** See folder [Session 4 - LSTM Sequence Classification](https://github.com/UKPLab/deeplearning4nlp-tutorial/tree/master/2016-11_Seminar/Session%204%20-%20LSTM%20Sequence%20Classification)
 
+LSTMs are a powerful model and became very popular in 2015 / 2016. 
+
+**Recommended Readings:**
+  * [RNN Effectivness](http://karpathy.github.io/2015/05/21/rnn-effectiveness/)
+    * [RNN Effectivness - Video](https://skillsmatter.com/skillscasts/6611-visualizing-and-understanding-recurrent-networks)
+  * [Understanding LSTMs](http://colah.github.io/posts/2015-08-Understanding-LSTMs/)
+  * [C224d Lecture 7](https://www.youtube.com/watch?v=rFVYTydGLr4)
+
 ## Code Session 4 - LSTM for Sequence Classification
 **Slides:** [pdf](https://github.com/UKPLab/deeplearning4nlp-tutorial/raw/master/2016-11_Seminar/Session%204%20-%20LSTM%20Sequence%20Classification/LSTM%20for%20Sequence%20Classification.pdf)
+
+The folder contains a Keras implementation to perfrom sequence classification using LSTM. We use the [GermEval 2014 dataset](https://sites.google.com/site/germeval2014ner/) for German NER. But you can adapt the code easily to any other sequence classification problem (POS, NER, Chunking etc.). Check the slides for more information.