revised css for better look

_config.yml

@@ -33,7 +33,7 @@ footer-links:
 
 # Enter your Disqus shortname (not your username) to enable commenting on posts
 # You can find your shortname on the Settings page of your Disqus account
-disqus: https://jwfugithubio.disqus.com
+disqus: jwfugithubio
 
 # Enter your Google Analytics web tracking code (e.g. UA-2110908-2) to activate tracking
 google_analytics: UA-73651212-1
@@ -52,8 +52,8 @@ baseurl: ""
 # !! You don't need to change any of the configuration flags below !!
 #
 
-markdown: redcarpet
-highlighter: pygments
+markdown: kramdown
+highlighter: rouge
 permalink: /:title/
 
 # The release of Jekyll Now that you're using

_posts/2016-2-10-Using-Jupyer-on-Amazon-EC2-for-HPC.md → _posts/2016-2-10-ipython-jupyter-on-ec2-for-hpc-p1.md

@@ -1,7 +1,8 @@
 ---
 layout: post
-title: Using Jupyter on Amazon EC2 for HPC
+title: IPython Jupyter on EC2 for HPC, Part 1
 ---
+**NOTE: I've made my AMI created using this procedure available publicly!  If you want to get going with IPython/Jupyter on EC2 super quickly and without the terminal see my guide [here]({{ site.baseurl }}/Jupyter-on-Amazon-EC2-Quick-Start/).**
 
 I attempted to use random forests as a first pass for [The Winton Stock Market Challenge](https://www.kaggle.com/c/the-winton-stock-market-challenge) on Kaggle and found that for any reasonable number of trees in the forest, I was unable to train the data in a reasonable amount of time.  Even though the solution itself was extremely unsuccessful, here's a short guide on how to do set up an EC2 instance to do large computations using Jupyter.
 
@@ -33,9 +34,10 @@ Copied from [here](http://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSGe
 
 5. To see your access key, choose Show User Security Credentials. Your credentials will look something like this:
 
-		Access Key ID: AKIAIOSFODNN7EXAMPLE
-
-		Secret Access Key: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
+```
+Access Key ID: AKIAIOSFODNN7EXAMPLE
+Secret Access Key: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
+```
 
 6. Choose Download Credentials, and store the keys in a secure location.
 

_posts/2016-2-10-ipython-jupyter-on-ec2-for-hpc-quickstart-p1.md

@@ -0,0 +1,12 @@
+---
+layout: post
+title: IPython Jupyter on EC2 for HPC Quickstart, Part 1
+---
+
+In my post [here]({{ site.baseurl }}/ipython-jupyter-on-ec2-for-hpc-p1/), I gave a procudure on how to create an EC2 instance from scratch and load IPython/Jupyter on it.  I've saved the image created from that and made it available for free so you can get going super quickly on 
+
+
+#Preliminaries
+1. Sign up for AWS.
+2. Lauch instance
+3. Select "Community AMIs"

_sass/_highlights.scss

@@ -7,7 +7,7 @@
   -webkit-box-shadow: 3px 3px rgba(0,0,0,0.1);
   box-shadow: 3px 3px rgba(0,0,0,0.1);
   margin: 20px 0 20px 0;
-  overflow: scroll;
+  overflow: auto;
 }
 
 code {