Update more.rst (#546)

* Update more.rst

Update the URLs

* Update more.rst

Author: 2wins

docs/user/more.rst

@@ -17,29 +17,29 @@ FAQ
 How to effectively learn TensorLayer
 ------------------------------------------
 No matter what stage you are in, we recommend you to spend just 10 minutes to
-read the source code of TensorLayer and the `Understand layer / Your layer <http://tensorlayer.readthedocs.io/en/stable/modules/layers.html>`_
+read the source code of TensorLayer and the `Understand layer / Your layer <http://tensorlayer.readthedocs.io/en/stable/modules/layers.html>`__
 in this website, you will find the abstract methods are very simple for everyone.
 Reading the source codes helps you to better understand TensorFlow and allows
 you to implement your own methods easily. For discussion, we recommend
-`Gitter <https://gitter.im/tensorlayer/Lobby#?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge>`_,
-`Help Wanted Issues <https://waffle.io/zsdonghao/tensorlayer>`_,
-`QQ group <https://github.com/zsdonghao/tensorlayer/blob/master/img/img_qq.png>`_
-and `Wechat group <https://github.com/shorxp/tensorlayer-chinese/blob/master/docs/wechat_group.md>`_.
+`Gitter <https://gitter.im/tensorlayer/Lobby#?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge>`__,
+`Help Wanted Issues <https://waffle.io/tensorlayer/tensorlayer>`__,
+`QQ group <https://github.com/zsdonghao/tensorlayer/blob/master/img/img_qq.png>`__
+and `Wechat group <https://github.com/shorxp/tensorlayer-chinese/blob/master/docs/wechat_group.md>`__.
 
 Beginner
 ^^^^^^^^^^^^^^
-For people who new to deep learning, the contirbutors provided a number of tutorials in this website, these tutorials will guide you to understand autoencoder, convolutional neural network, recurrent neural network, word embedding and deep reinforcement learning and etc. If your already understand the basic of deep learning, we recommend you to skip the tutorials and read the example codes on `Github <https://github.com/zsdonghao/tensorlayer>`_ , then implement an example from scratch.
+For people who new to deep learning, the contirbutors provided a number of tutorials in this website, these tutorials will guide you to understand autoencoder, convolutional neural network, recurrent neural network, word embedding and deep reinforcement learning and etc. If your already understand the basic of deep learning, we recommend you to skip the tutorials and read the example codes on `Github <https://github.com/tensorlayer/tensorlayer>`__ , then implement an example from scratch.
 
 Engineer
 ^^^^^^^^^^^^^
 For people from industry, the contirbutors provided mass format-consistent examples covering computer vision, natural language processing and reinforcement learning. Besides, there are also many TensorFlow users already implemented product-level examples including image captioning, semantic/instance segmentation, machine translation, chatbot and etc, which can be found online.
-It is worth noting that a wrapper especially for computer vision `Tf-Slim <https://github.com/tensorflow/models/tree/master/slim#Pretrained>`_ can be connected with TensorLayer seamlessly.
+It is worth noting that a wrapper especially for computer vision `Tf-Slim <https://github.com/tensorflow/models/tree/master/slim#Pretrained>`__ can be connected with TensorLayer seamlessly.
 Therefore, you may able to find the examples that can be used in your project.
 
 Researcher
 ^^^^^^^^^^^^^
 For people from academic, TensorLayer was originally developed by PhD students who facing issues with other libraries on implement novel algorithm. Installing TensorLayer in editable mode is recommended, so you can extend your methods in TensorLayer.
-For researches related to image such as image captioning, visual QA and etc, you may find it is very helpful to use the existing `Tf-Slim pre-trained models <https://github.com/tensorflow/models/tree/master/slim#Pretrained>`_ with TensorLayer (a specially layer for connecting Tf-Slim is provided).
+For researches related to image such as image captioning, visual QA and etc, you may find it is very helpful to use the existing `Tf-Slim pre-trained models <https://github.com/tensorflow/models/tree/master/slim#Pretrained>`__ with TensorLayer (a specially layer for connecting Tf-Slim is provided).
 
 
 Exclude some layers from training