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@@ -22,7 +22,7 @@ I would continue adding papers to this roadmap.
 
 ## 1.0 Book
 
-**[0]** Bengio, Yoshua, Ian J. Goodfellow, and Aaron Courville. "**Deep learning**." An MIT Press book. (2015). [[pdf]](https://github.com/HFTrader/DeepLearningBook/raw/master/DeepLearningBook.pdf) **(Deep Learning Bible, you can read this book while reading following papers.)** :star::star::star::star::star:
+**[0]** Bengio, Yoshua, Ian J. Goodfellow, and Aaron Courville. "**Deep learning**." An MIT Press book. (2015). [[Read book]](http://www.deeplearningbook.org/) **(Deep Learning Bible, you can read this book while reading following papers.)** :star::star::star::star::star:
 
 ## 1.1 Survey
 
@@ -60,7 +60,7 @@ I would continue adding papers to this roadmap.
 
 >After reading above papers, you will have a basic understanding of the Deep Learning history, the basic architectures of Deep Learning model(including CNN, RNN, LSTM) and how deep learning can be applied to image and speech recognition issues. The following papers will take you in-depth understanding of the Deep Learning method, Deep Learning in different areas of application and the frontiers. I suggest that you can choose the following papers based on your interests and research direction.
 
-#2 Deep Learning Method
+# 2 Deep Learning Method
 
 ## 2.1 Model