update doc

_build/html/_sources/index.rst.txt

@@ -7,14 +7,14 @@ Get Started with xLearn !
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 xLearn is a *high-performance*, *easy-to-use*, and *scalable* machine learning package, 
-which can be used to solve large-scale machine learning problems, especially for for solving 
+which can be used to solve large-scale machine learning problems, especially for for the 
 problems on large-scale sparse data, which is very common in scenes like CTR prediction and 
-recommender system. If you are the user of liblinear, libfm, or libffm, now xLearn the your 
-another better choice. This is because xLearn handles all of these models in a uniform platform 
-and provides better performance and scalability.
+recommender system. If you are the user of liblinear, libfm, or libffm, now xLearn is your 
+another better choice. This is because xLearn handles all of these models in an uniform 
+platform and provides better performance and scalability compared to its competitors.
 
-This is a quick start tutorial showing snippets for you to quickly try out xLearn on a small demo 
-dataset (Criteo CTR) for a binary classfication task.
+This is a quick start tutorial showing snippets for you to quickly try out xLearn on a small 
+demo dataset (Criteo CTR prediction) for a binary classfication task.
 
 Link to the Other Helpful Resources
 ----------------------------------------

_build/html/index.html

@@ -161,13 +161,13 @@
   <div class="section" id="get-started-with-xlearn">
 <h1>Get Started with xLearn !<a class="headerlink" href="#get-started-with-xlearn" title="Permalink to this headline">¶</a></h1>
 <p>xLearn is a <em>high-performance</em>, <em>easy-to-use</em>, and <em>scalable</em> machine learning package,
-which can be used to solve large-scale machine learning problems, especially for for solving
+which can be used to solve large-scale machine learning problems, especially for for the
 problems on large-scale sparse data, which is very common in scenes like CTR prediction and
-recommender system. If you are the user of liblinear, libfm, or libffm, now xLearn the your
-another better choice. This is because xLearn handles all of these models in a uniform platform
-and provides better performance and scalability.</p>
-<p>This is a quick start tutorial showing snippets for you to quickly try out xLearn on a small demo
-dataset (Criteo CTR) for a binary classfication task.</p>
+recommender system. If you are the user of liblinear, libfm, or libffm, now xLearn is your
+another better choice. This is because xLearn handles all of these models in an uniform
+platform and provides better performance and scalability compared to its competitors.</p>
+<p>This is a quick start tutorial showing snippets for you to quickly try out xLearn on a small
+demo dataset (Criteo CTR prediction) for a binary classfication task.</p>
 <div class="section" id="link-to-the-other-helpful-resources">
 <h2>Link to the Other Helpful Resources<a class="headerlink" href="#link-to-the-other-helpful-resources" title="Permalink to this headline">¶</a></h2>
 <blockquote>

index.rst

@@ -9,9 +9,9 @@ Get Started with xLearn !
 xLearn is a *high-performance*, *easy-to-use*, and *scalable* machine learning package, 
 which can be used to solve large-scale machine learning problems, especially for for the 
 problems on large-scale sparse data, which is very common in scenes like CTR prediction and 
-recommender system. If you are the user of liblinear, libfm, or libffm, now xLearn the your 
+recommender system. If you are the user of liblinear, libfm, or libffm, now xLearn is your 
 another better choice. This is because xLearn handles all of these models in an uniform 
-platform and provides better performance and scalability.
+platform and provides better performance and scalability compared to its competitors.
 
 This is a quick start tutorial showing snippets for you to quickly try out xLearn on a small 
 demo dataset (Criteo CTR prediction) for a binary classfication task.