Some small changes to the main landing page.

index.html

@@ -42,8 +42,9 @@ <H2>The workbench for machine learning</h2>
 
 							</p>
             						<a href="https://waikato.github.io/weka-wiki/downloading_weka/" class="button">Download and install</a>
+							<a href="https://waikato.github.io/weka-wiki/documentation" class="button scrolly">Docs</a>
 							<a href="./courses.html" class="button scrolly">Courses</a>
-					<a href="./book.html" class="button scrolly">Book</a>
+							<a href="./book.html" class="button scrolly">Book</a>
 						</div>
 					</div>
 				</div>
@@ -75,37 +76,37 @@ <h1 name="GetStart" id="GetStart">Getting Started</h1>
 			<div class="container">
 				<header>
 					<h2 name="learn" id ="learn" >Machine Learning without Programming</h2>
-					<p>Weka can be used to build machine learning pipelines, train classifiers, and run evaluations without having to write a single line of code.</p>
+					<p>Weka can be used to build machine learning pipelines, train classifiers, and run evaluations without having to write a single line of code:</p>
 
 				</header>
 				<div class="row">
 					<div class="col-4 col-6-medium col-12-small">
 						<article class="box style2">
-							<a href="" class="image featured"><img src="https://waikato.github.io/weka-site/images/Explorer-1.png" alt=""/></a>
-							<h3><a href="">Open a Dataset</a></h3>
-							<p>First, we open the dataset that we would like to evaluate.</p>
+							<span class="image fit"><img src="https://waikato.github.io/weka-site/images/Explorer-1.png" alt=""/></span>
+							<h3>Open a dataset</h3>
+							<p>First, we open the <a href="https://waikato.github.io/weka-wiki/datasets/" target="_blank">dataset</a> that we would like to evaluate.</p>
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 					<div class="col-4 col-6-medium col-12-small">
 						<article class="box style2">
-							<a href="" class="image featured"><img src="https://waikato.github.io/weka-site/images/Explorer-2.png" alt=""/></a>
-							<h3><a href="">Choose a classifier</a></h3>
+							<span class="image fit"><img src="https://waikato.github.io/weka-site/images/Explorer-2.png" alt=""/></span>
+							<h3>Choose a classifier</h3>
 							<p> Second, we select a learning algorithm to use, e.g., the J48 classifier, which learns decision trees.</p>
 							</article>
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 					<div class="col-4 col-6-medium col-12-small">
 						<article class="box style2">
-							<a href="#" class="image featured"><img src="https://waikato.github.io/weka-site/images/Explorer-3.png" alt="" /></a>
-							<h3><a href="">Evaluate predictive accuracy</a></h3>
+							<span class="image fit"><img src="https://waikato.github.io/weka-site/images/Explorer-3.png" alt="" /></span>
+							<h3>Evaluate predictive accuracy</h3>
 							<p>Finally, we run a 10-fold cross-validation evaluation and obtain an estimate of predictive performance.</p>
 						</article>
 					</div>
 
 				<footer>
-					<p>And programmers can easily implement this pipeline in Java:</p>
+					<p>Note that programmers can also easily implement this pipeline using Weka's Java API:</p>
 					<p>
 					<iframe
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