updates for jb version

Author: nocomplexity

MLlearningresources.rst

@@ -10,15 +10,22 @@ Of course also only resources that are open, so only resources published
 using a Creative Commons license (cc-by mostly) or other real open
 licenses are included. So all references are open access resources.
 
--   Natural Language Processing with Python, <http://www.nltk.org/book/>
+-  Natural Language Processing with Python, <http://www.nltk.org/book/>   
 
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--   Advanced NLP with spaCY, <https://course.spacy.io/>
 
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+-  Advanced NLP with spaCY, <https://course.spacy.io/>    
 
--   NLP concepts with spaCy (notebook)
-    <https://gist.github.com/nocomplexity/b7c4c0aa5a0b53f4f5ff1c4784084be6>
 
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+-  NLP concepts with spaCy (notebook), <https://gist.github.com/nocomplexity/b7c4c0aa5a0b53f4f5ff1c4784084be6>   
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NLPlearningresources.md

@@ -3,7 +3,9 @@
                 
 # Free and Open Machine Learning
 
-Great that you are interested in this open collaboration project.
+Great that you are interested in this open collaboration project!
+
+The latest online version can be found here: https://nocomplexity.com/documents/fossml/
 
 This project is all about collaborative learning on applying FOSS Machine Learning.
 This project is an open research project. It is open for all to join.

NLPlearningresources.rst

@@ -48,7 +48,7 @@ You should also be aware of the important difference between:
 -   Architecture building Blocks and
 -   Solution building blocks
 
-![ML Architecture Building Blocks vs SBBs](/images/abb-sbb.png){.align-center}
+![ML Architecture Building Blocks vs SBBs](/images/abb-sbb.png)
 
 This reference architecture for machine learning describes architecture
 building blocks. So you could use this reference architecture and ask
@@ -99,7 +99,7 @@ steps. These steps are:
     you need is to search for more training data within this iterative
     loop.
 
-![Machine Learning Process](/images/ml-process.png){.align-center}
+![Machine Learning Process](/images/ml-process.png)
 
 You need to improve your machine learning model after the first test.
 Improving can be done using more training data or by making model
@@ -126,7 +126,7 @@ and requirements are needed.
 The way to develop a machine learning architecture is outlined in the
 figure below.
 
-![Machine Learning Architecture Process](/images/solutionsteps-overview.png){.align-center}
+![Machine Learning Architecture Process](/images/solutionsteps-overview.png)
 
 In essence developing an architecture for machine learning is equal as
 for every other system. But some aspects require special attention.
@@ -262,7 +262,7 @@ overview of aspects regarding machine learning. Using this model gives
 you a head start when developing your specific machine learning
 solution.
 
-![Machine Learning Architecture Building Blocks](/images/ml-reference-architecture.png){.align-center}
+![Machine Learning Architecture Building Blocks](/images/ml-reference-architecture.png)
 
 Conceptual overview of machine learning reference architecture