diff --git a/authors/rhys-compton.xml b/authors/rhys-compton.xml
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+
+WEKA Blog (Posts by Rhys Compton)https://waikato.github.io/weka-blog/enThu, 26 Nov 2020 06:29:11 GMTNikola (getnikola.com)http://blogs.law.harvard.edu/tech/rssNew WekaDeeplearning4j Release - CNN explorer, saliency maps, progress manager, and model summarieshttps://waikato.github.io/weka-blog/posts/2020-11-26-wekaDeeplearning4j-1.7.0/Rhys Compton<div><p>A new version of WekaDeeplearning4j, version 1.7.0, is available!</p>
+<!-- TEASER_EN -->
+<p></p>
+<p>### Dl4j Inference Panel & Dl4jCNNExplorer
+One major addition in <strong>WekaDeeplearning4j</strong> v1.7.0 is the new <strong>Dl4jCNNExplorer</strong> and the
+associated GUI <strong>Dl4j Inference Panel</strong>. This brings real-time inference to the WEKA universe,
+allowing you to quickly run an image classification CNN model on an image without having to
+load an entire <cite>.arff</cite> file.</p>
+<p>The <strong>Dl4jCNNExplorer</strong> supports both a custom-trained <cite>Dl4jMlpClassifier</cite> and a model from
+the Model Zoo, so it can be used to verify your model's prediction capabilities
+or simply play around with pretrained models and explore what state-of-the-art
+architectures may work best for your domain.</p>
+<p>Check out the [usage example](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/">https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/</a>)
+to see how easy it is to get started.</p>
+<p>### Saliency Map Generation with ScoreCAM
+Another exciting new feature is the implementation of <strong>ScoreCAM</strong>, a saliency map generation technique.
+This can be accessed through the <cite>Dl4jCNNExplorer</cite>, allowing you to not only perform prediction on an image,
+but look at <em>what</em> in the image your model was using for prediction.</p>
+<p>This can be invoked from the command-line, although the best user experience is to be had from the GUI using the
+<strong>Saliency Map Viewer</strong>, which allows you to quickly customize the ScoreCAM target classes.</p>
+<p>Check out the [usage example](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/#example-4-saliency-map-generation">https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/#example-4-saliency-map-generation</a>)
+to see what new insights can be brought to your workflow.</p>
+<p>### Progress Manager</p>
+<p></p>
+<p>We've created a simple---but effective---progress bar and added this to the long-running tasks
+(model training, feature extraction, etc.). This provides a graphical indicator of progress and remaining
+ETA for the current job so will make WEKA more usable for large jobs.</p>
+<p>### Model Summaries</p>
+<p>We've also added [model summaries](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/user-guide/model-zoo/#model-summaries">https://deeplearning.cms.waikato.ac.nz/user-guide/model-zoo/#model-summaries</a>)
+to the documentation, which specify the different models and their layers. This can be useful for designing
+your own architectures or with the <cite>Dl4jMlpFilter</cite>, when using intermediary layers for feature extraction.</p></div>githubhttps://waikato.github.io/weka-blog/posts/2020-11-26-wekaDeeplearning4j-1.7.0/Thu, 26 Nov 2020 06:06:00 GMT
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+
+Posts by Rhys Compton | WEKA Blog
+
+
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+
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+
+
+
+Skip to main content
+
+
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diff --git a/categories/cat_packages.xml b/categories/cat_packages.xml
index daa77a9..90e0ee4 100644
--- a/categories/cat_packages.xml
+++ b/categories/cat_packages.xml
@@ -1,3 +1,33 @@
-WEKA Blog (Posts about packages)https://waikato.github.io/weka-blog/enSat, 04 Jul 2020 08:37:15 GMTNikola (getnikola.com)http://blogs.law.harvard.edu/tech/rssNew WekaDeeplearning4j Release - Pretrained Models, Feature Extraction Update, and morehttps://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/Eibe Frank<div><p>A new version of WekaDeeplearning4j, version 1.6.0, has just been released and brings with it a bunch of exciting new features.</p>
+WEKA Blog (Posts about packages)https://waikato.github.io/weka-blog/enThu, 26 Nov 2020 06:29:11 GMTNikola (getnikola.com)http://blogs.law.harvard.edu/tech/rssNew WekaDeeplearning4j Release - CNN explorer, saliency maps, progress manager, and model summarieshttps://waikato.github.io/weka-blog/posts/2020-11-26-wekaDeeplearning4j-1.7.0/Rhys Compton<div><p>A new version of WekaDeeplearning4j, version 1.7.0, is available!</p>
+<!-- TEASER_EN -->
+<p></p>
+<p>### Dl4j Inference Panel & Dl4jCNNExplorer
+One major addition in <strong>WekaDeeplearning4j</strong> v1.7.0 is the new <strong>Dl4jCNNExplorer</strong> and the
+associated GUI <strong>Dl4j Inference Panel</strong>. This brings real-time inference to the WEKA universe,
+allowing you to quickly run an image classification CNN model on an image without having to
+load an entire <cite>.arff</cite> file.</p>
+<p>The <strong>Dl4jCNNExplorer</strong> supports both a custom-trained <cite>Dl4jMlpClassifier</cite> and a model from
+the Model Zoo, so it can be used to verify your model's prediction capabilities
+or simply play around with pretrained models and explore what state-of-the-art
+architectures may work best for your domain.</p>
+<p>Check out the [usage example](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/">https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/</a>)
+to see how easy it is to get started.</p>
+<p>### Saliency Map Generation with ScoreCAM
+Another exciting new feature is the implementation of <strong>ScoreCAM</strong>, a saliency map generation technique.
+This can be accessed through the <cite>Dl4jCNNExplorer</cite>, allowing you to not only perform prediction on an image,
+but look at <em>what</em> in the image your model was using for prediction.</p>
+<p>This can be invoked from the command-line, although the best user experience is to be had from the GUI using the
+<strong>Saliency Map Viewer</strong>, which allows you to quickly customize the ScoreCAM target classes.</p>
+<p>Check out the [usage example](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/#example-4-saliency-map-generation">https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/#example-4-saliency-map-generation</a>)
+to see what new insights can be brought to your workflow.</p>
+<p>### Progress Manager</p>
+<p></p>
+<p>We've created a simple---but effective---progress bar and added this to the long-running tasks
+(model training, feature extraction, etc.). This provides a graphical indicator of progress and remaining
+ETA for the current job so will make WEKA more usable for large jobs.</p>
+<p>### Model Summaries</p>
+<p>We've also added [model summaries](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/user-guide/model-zoo/#model-summaries">https://deeplearning.cms.waikato.ac.nz/user-guide/model-zoo/#model-summaries</a>)
+to the documentation, which specify the different models and their layers. This can be useful for designing
+your own architectures or with the <cite>Dl4jMlpFilter</cite>, when using intermediary layers for feature extraction.</p></div>githubhttps://waikato.github.io/weka-blog/posts/2020-11-26-wekaDeeplearning4j-1.7.0/Thu, 26 Nov 2020 06:06:00 GMTNew WekaDeeplearning4j Release - Pretrained Models, Feature Extraction Update, and morehttps://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/Eibe Frank<div><p>A new version of WekaDeeplearning4j, version 1.6.0, has just been released and brings with it a bunch of exciting new features.</p>
<p><a href="https://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/">Read more…</a> (1 min remaining to read)</p></div>githubhttps://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/Sat, 04 Jul 2020 06:06:00 GMT
\ No newline at end of file
diff --git a/categories/cat_packages/index.html b/categories/cat_packages/index.html
index 052341a..4d7581f 100644
--- a/categories/cat_packages/index.html
+++ b/categories/cat_packages/index.html
@@ -68,6 +68,9 @@
diff --git a/categories/github.xml b/categories/github.xml
index 0da6ce1..2608ff0 100644
--- a/categories/github.xml
+++ b/categories/github.xml
@@ -1,5 +1,35 @@
-WEKA Blog (Posts about github)https://waikato.github.io/weka-blog/enSat, 04 Jul 2020 08:37:15 GMTNikola (getnikola.com)http://blogs.law.harvard.edu/tech/rssNew WekaDeeplearning4j Release - Pretrained Models, Feature Extraction Update, and morehttps://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/Eibe Frank<div><p>A new version of WekaDeeplearning4j, version 1.6.0, has just been released and brings with it a bunch of exciting new features.</p>
+WEKA Blog (Posts about github)https://waikato.github.io/weka-blog/enThu, 26 Nov 2020 06:29:11 GMTNikola (getnikola.com)http://blogs.law.harvard.edu/tech/rssNew WekaDeeplearning4j Release - CNN explorer, saliency maps, progress manager, and model summarieshttps://waikato.github.io/weka-blog/posts/2020-11-26-wekaDeeplearning4j-1.7.0/Rhys Compton<div><p>A new version of WekaDeeplearning4j, version 1.7.0, is available!</p>
+<!-- TEASER_EN -->
+<p></p>
+<p>### Dl4j Inference Panel & Dl4jCNNExplorer
+One major addition in <strong>WekaDeeplearning4j</strong> v1.7.0 is the new <strong>Dl4jCNNExplorer</strong> and the
+associated GUI <strong>Dl4j Inference Panel</strong>. This brings real-time inference to the WEKA universe,
+allowing you to quickly run an image classification CNN model on an image without having to
+load an entire <cite>.arff</cite> file.</p>
+<p>The <strong>Dl4jCNNExplorer</strong> supports both a custom-trained <cite>Dl4jMlpClassifier</cite> and a model from
+the Model Zoo, so it can be used to verify your model's prediction capabilities
+or simply play around with pretrained models and explore what state-of-the-art
+architectures may work best for your domain.</p>
+<p>Check out the [usage example](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/">https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/</a>)
+to see how easy it is to get started.</p>
+<p>### Saliency Map Generation with ScoreCAM
+Another exciting new feature is the implementation of <strong>ScoreCAM</strong>, a saliency map generation technique.
+This can be accessed through the <cite>Dl4jCNNExplorer</cite>, allowing you to not only perform prediction on an image,
+but look at <em>what</em> in the image your model was using for prediction.</p>
+<p>This can be invoked from the command-line, although the best user experience is to be had from the GUI using the
+<strong>Saliency Map Viewer</strong>, which allows you to quickly customize the ScoreCAM target classes.</p>
+<p>Check out the [usage example](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/#example-4-saliency-map-generation">https://deeplearning.cms.waikato.ac.nz/examples/dl4j-inference/#example-4-saliency-map-generation</a>)
+to see what new insights can be brought to your workflow.</p>
+<p>### Progress Manager</p>
+<p></p>
+<p>We've created a simple---but effective---progress bar and added this to the long-running tasks
+(model training, feature extraction, etc.). This provides a graphical indicator of progress and remaining
+ETA for the current job so will make WEKA more usable for large jobs.</p>
+<p>### Model Summaries</p>
+<p>We've also added [model summaries](<a class="reference external" href="https://deeplearning.cms.waikato.ac.nz/user-guide/model-zoo/#model-summaries">https://deeplearning.cms.waikato.ac.nz/user-guide/model-zoo/#model-summaries</a>)
+to the documentation, which specify the different models and their layers. This can be useful for designing
+your own architectures or with the <cite>Dl4jMlpFilter</cite>, when using intermediary layers for feature extraction.</p></div>githubhttps://waikato.github.io/weka-blog/posts/2020-11-26-wekaDeeplearning4j-1.7.0/Thu, 26 Nov 2020 06:06:00 GMTNew WekaDeeplearning4j Release - Pretrained Models, Feature Extraction Update, and morehttps://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/Eibe Frank<div><p>A new version of WekaDeeplearning4j, version 1.6.0, has just been released and brings with it a bunch of exciting new features.</p>
<p><a href="https://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/">Read more…</a> (1 min remaining to read)</p></div>githubhttps://waikato.github.io/weka-blog/posts/2020-07-04-wekaDeeplearning4j-1.6.0/Sat, 04 Jul 2020 06:06:00 GMTWeka Debian packageshttps://waikato.github.io/weka-blog/posts/2019-09-23-weka-debian-packages/FracPete<div><p>Users installing Weka on Linux must have always felt left out
a bit, with no installer available, instead having to deal with
just a ZIP file. For power users, that would not have mattered,
diff --git a/categories/github/index.html b/categories/github/index.html
index d3b0c89..88bc38b 100644
--- a/categories/github/index.html
+++ b/categories/github/index.html
@@ -68,6 +68,9 @@