package water.api;

/**
 * Summary page referencing all tutorials.
 *
 * @author michal
 */
public class Tutorials extends HTMLOnlyRequest {

  @Override protected String build(Response response) {
    return "<div class='container'><div class='hero-unit' style='overflow: hidden'>"
    + "<style scoped='scoped'>"
    + "  h2 { font-size:18px; }"
    + "  p { font-size:16px; }"
    + "</style>"
    + "<h1>H<sub>2</sub>O Tutorials</h1>"
    + "<blockquote><small>A unique way to explore H<sub>2</sub>O</small></blockquote>"

    + "</div>"
    + "<div class='row'>"

    + "<div class='span3 col'>"
    + "  <h2>Random Forest</h2>"
    +   "<p>Random Forest is a classical machine learning algorithm serving for data classification. Learn how to use it with H<sub>2</sub>O.</it></p>"
    +   "<a href='/TutorialRFIris.html' class='btn btn-primary'>Try it!</a>"
    + "</div>"

    + "<div class='span3 col'>"
    +   "<h2>GLM</h2>"
    +   "<p>Generalized linear model is a generalization of linear regression. Experience its unique power on the top of H<sub>2</sub>O.</p>"
    +   "<a href='/TutorialGLMProstate.html' class='btn btn-primary'>Try it!</a>"
    + "</div>"

    + "<div class='span3 col'>"
    + "<h2>K-means</h2>"
    + "<p>Perform cluster analysis with H<sub>2</sub>O and K-means algorithm. H<sub>2</sub>O implements K-means, a highly scalable version.</p>"
    +   "<a href='/TutorialKMeans.html' class='btn btn-primary'>Try it!</a>"
    + "</div>"

    + "<div class='span3 col'>"
    + "<h2>Deep Learning</h2>"
    + "<p>Use H<sub>2</sub>O to model high-level abstractions in data by using architectures composed of multiple non-linear transformations.</p>"
    +   "<a href='/TutorialDeepLearning.html' class='btn btn-primary'>Try it!</a>"
    + "</div>"

    + "</div>"
    + "</div>";
  }
}

@@ -699,36 +699,38 @@
 thm 
-serving for data classificat
+for classification and regress
 ion.
@@ -1043,12 +1043,8 @@
  on 
-the 
 top 
@@ -1280,56 +1280,19 @@
 ub%3EO
- and K-means algorithm. H%3Csub%3E2%3C/sub%3EO implement
+. It employ
 s K-
@@ -1320,15 +1320,28 @@
 ble 
-version
+clustering algorithm
 .%3C/p
@@ -1513,12 +1513,8 @@
 %22%3Cp%3E
-Use 
 H%3Csu
@@ -1527,17 +1527,43 @@
 ub%3EO
- to
+'s distributed Deep Learning
  model
+s
  hig
@@ -1595,77 +1595,43 @@
 ata 
-by using architectures composed of multiple non-linear transformation
+with deep artificial neural network
 s.%3C/

Clean up Tutorials page.