diff --git a/README.rst b/README.rst
index d3bc93d125426a04fdb8c913ce02587877428886..997dc7058c5f1497f3559db5fcc90652d238afdd 100644
--- a/README.rst
+++ b/README.rst
@@ -175,9 +175,9 @@ Algorithm Benchmark
 
 **Comparison of all implemented models** are made available below:
 
-(\ `Figure <https://raw.githubusercontent.com/yzhao062/Pyod/master/examples/ALL.png>`_\ ,
-`compare_all_models.py <https://github.com/yzhao062/Pyod/blob/master/examples/compare_all_models.py>`_\ ,
-`Jupyter Notebooks <https://mybinder.org/v2/gh/yzhao062/Pyod/master>`_\ ):
+(\ `Figure <https://raw.githubusercontent.com/yzhao062/pyod/master/examples/ALL.png>`_\ ,
+`compare_all_models.py <https://github.com/yzhao062/pyod/blob/master/examples/compare_all_models.py>`_\ ,
+`Jupyter Notebooks <https://mybinder.org/v2/gh/yzhao062/pyod/master>`_\ ):
 
 For Jupyter Notebooks, please navigate to **"/notebooks/Compare All Models.ipynb"**
 
diff --git a/docs/index.rst b/docs/index.rst
index 38f1c4476e999aa922d5048fd7c780e23f4a5eae..308b69417fd170d82d70b12202b1847e5d185e00 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -73,13 +73,12 @@ Welcome to PyOD documentation!
 
 ----
 
-**Py**\ thon \ **O**\ utlier \ **D**\ etection (PyOD) is a comprehensive and
-scalable **Python toolkit** for **detecting outlying objects** in multivariate data.
-This exciting yet challenging field is commonly referred as `Outlier Detection <https://en.wikipedia.org/wiki/Anomaly_detection>`_
+PyOD is a comprehensive and scalable **Python toolkit** for **detecting outlying objects** in
+multivariate data. This exciting yet challenging field is commonly referred as
+`Outlier Detection <https://en.wikipedia.org/wiki/Anomaly_detection>`_
 or `Anomaly Detection <https://en.wikipedia.org/wiki/Anomaly_detection>`_.
-
-Since 2017, PyOD has been successfully used in various academic researches
-:cite:`a-zhao2018xgbod,a-zhao2018dcso` and commercial products. PyOD is featured for:
+Since 2017, PyOD has been successfully used in various academic researches :cite:`a-zhao2018xgbod,a-zhao2018dcso` and commercial products.
+PyOD is featured for:
 
 - **Unified APIs, detailed documentation, and interactive examples** across various algorithms.
 - **Advanced models**, including **Neural Networks/Deep Learning** and **Outlier Ensembles**.