resources added

README.md

@@ -4,14 +4,9 @@
 [![PyPI](https://badge.fury.io/py/tensorflow.svg)](https://badge.fury.io/py/trtokenizer)
 
 TrTokenizer is a complete solution for Turkish sentence and word tokenization with extensively-covering language
-conventions.
-
-If you think that Natural language models always need robust, fast, and accurate tokenizers, be sure that you are at the
-the right place now.
-
-Sentence tokenization approach uses non-prefix keyword given in 'tr_non_suffixes' file. This file can be expanded if
+conventions. If you think that Natural language models always need robust, fast, and accurate tokenizers, be sure that you are at the
+the right place now. Sentence tokenization approach uses non-prefix keyword given in 'tr_non_suffixes' file. This file can be expanded if
 required, for developer convenience lines start with # symbol are evaluated as comments.
-
 Designed regular expressions are pre-compiled to speed-up the performance.
 
 ## Install
@@ -42,4 +37,9 @@ word_tokenizer_object.tokenize(<given sentence as string>)
 - Release platform specific shared dynamic libraries (Done, build/tr_tokenizer.cpython-38-x86_64-linux-gnu.so, only for
   Debian Linux with gcc compiler)
 - Limitations
-- Prepare a simple guide for contribution
+- Prepare a simple guide for contribution
+
+## Resources
+
+* [Speech and Language Processing](https://web.stanford.edu/~jurafsky/slp3/)
+* [Bogazici University CMPE-561](https://www.cmpe.boun.edu.tr/tr/courses/cmpe561)