update doc

_build/html/_sources/index.rst.txt

@@ -7,11 +7,11 @@ 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 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.
+which can be used to solve large-scale machine learning problems, especially 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 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 prediction) for a binary classfication task.

_build/html/index.html

@@ -161,11 +161,11 @@
   <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 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 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>
+which can be used to solve large-scale machine learning problems, especially 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 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">

index.rst

@@ -7,11 +7,11 @@ 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 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.
+which can be used to solve large-scale machine learning problems, especially 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 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 prediction) for a binary classfication task.